/*M///////////////////////////////////////////////////////////////////////////////////////
 //
 //  IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING.
 //
 //  By downloading, copying, installing or using the software you agree to this license.
 //  If you do not agree to this license, do not download, install,
 //  copy or use the software.
 //
 //
 //                           License Agreement
 //                For Open Source Computer Vision Library
 //
 // Copyright (C) 2013, Biagio Montesano, all rights reserved.
 // Third party copyrights are property of their respective owners.
 //
 // Redistribution and use in source and binary forms, with or without modification,
 // are permitted provided that the following conditions are met:
 //
 //   * Redistribution's of source code must retain the above copyright notice,
 //     this list of conditions and the following disclaimer.
 //
 //   * Redistribution's in binary form must reproduce the above copyright notice,
 //     this list of conditions and the following disclaimer in the documentation
 //     and/or other materials provided with the distribution.
 //
 //   * The name of the copyright holders may not be used to endorse or promote products
 //     derived from this software without specific prior written permission.
 //
 // This software is provided by the copyright holders and contributors "as is" and
 // any express or implied warranties, including, but not limited to, the implied
 // warranties of merchantability and fitness for a particular purpose are disclaimed.
 // In no event shall the Intel Corporation or contributors be liable for any direct,
 // indirect, incidental, special, exemplary, or consequential damages
 // (including, but not limited to, procurement of substitute goods or services;
 // loss of use, data, or profits; or business interruption) however caused
 // and on any theory of liability, whether in contract, strict liability,
 // or tort (including negligence or otherwise) arising in any way out of
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 //M*/

#include "precomp.hpp"

#ifdef _MSC_VER
    #if (_MSC_VER <= 1700)
        /* This function rounds x to the nearest integer, but rounds halfway cases away from zero. */
        static inline double round(double x)
        {
            if (x < 0.0)
                return ceil(x - 0.5);
            else
                return floor(x + 0.5);
        }
    #endif
#endif

#define NUM_OF_BANDS 9
#define Horizontal  255//if |dx|<|dy|;
#define Vertical    0//if |dy|<=|dx|;
#define UpDir       1
#define RightDir    2
#define DownDir     3
#define LeftDir     4
#define TryTime     6
#define SkipEdgePoint 2

//using namespace cv;
namespace cv
{
namespace line_descriptor
{

/* combinations of internal indeces for binary descriptor extractor */
static const int combinations[32][2] =
{
{ 0, 1 },
{ 0, 2 },
{ 0, 3 },
{ 0, 4 },
{ 0, 5 },
{ 0, 6 },
{ 1, 2 },
{ 1, 3 },
{ 1, 4 },
{ 1, 5 },
{ 1, 6 },
{ 2, 3 },
{ 2, 4 },
{ 2, 5 },
{ 2, 6 },
{ 2, 7 },
{ 2, 8 },
{ 3, 4 },
{ 3, 5 },
{ 3, 6 },
{ 3, 7 },
{ 3, 8 },
{ 4, 5 },
{ 4, 6 },
{ 4, 7 },
{ 4, 8 },
{ 5, 6 },
{ 5, 7 },
{ 5, 8 },
{ 6, 7 },
{ 6, 8 },
{ 7, 8 } };

/* return default parameters */
BinaryDescriptor::Params::Params()
{
  numOfOctave_ = 1;
  widthOfBand_ = 7;
  reductionRatio = 2;
  ksize_ = 5;
}

/* setters and getters */
int BinaryDescriptor::getNumOfOctaves()
{
  return params.numOfOctave_;
}

void BinaryDescriptor::setNumOfOctaves( int octaves )
{
  params.numOfOctave_ = octaves;
}

int BinaryDescriptor::getWidthOfBand()
{
  return params.widthOfBand_;
}

void BinaryDescriptor::setWidthOfBand( int width )
{
  params.widthOfBand_ = width;

  /* reserve enough space for EDLine objects and images in Gaussian pyramid */
  edLineVec_.resize( params.numOfOctave_ );
  images_sizes.resize( params.numOfOctave_ );

  for ( int i = 0; i < params.numOfOctave_; i++ )
    edLineVec_[i] = Ptr < EDLineDetector > ( new EDLineDetector() );

  /* prepare a vector to host local weights F_l*/
  gaussCoefL_.resize( params.widthOfBand_ * 3 );

  /* compute center of central band (every computation involves 2-3 bands) */
  double u = ( params.widthOfBand_ * 3 - 1 ) / 2;

  /* compute exponential part of F_l */
  double sigma = ( params.widthOfBand_ * 2 + 1 ) / 2;  // (widthOfBand_*2+1)/2;
  double invsigma2 = -1 / ( 2 * sigma * sigma );

  /* compute all local weights */
  double dis;
  for ( int i = 0; i < params.widthOfBand_ * 3; i++ )
  {
    dis = i - u;
    gaussCoefL_[i] = exp( dis * dis * invsigma2 );
  }

  /* prepare a vector for global weights F_g*/
  gaussCoefG_.resize( NUM_OF_BANDS * params.widthOfBand_ );

  /* compute center of LSR */
  u = ( NUM_OF_BANDS * params.widthOfBand_ - 1 ) / 2;

  /* compute exponential part of F_g */
  sigma = u;
  invsigma2 = -1 / ( 2 * sigma * sigma );
  for ( int i = 0; i < NUM_OF_BANDS * params.widthOfBand_; i++ )
  {
    dis = i - u;
    gaussCoefG_[i] = exp( dis * dis * invsigma2 );
  }
}

int BinaryDescriptor::getReductionRatio()
{
  return params.reductionRatio;
}

void BinaryDescriptor::setReductionRatio( int rRatio )
{
  params.reductionRatio = rRatio;
}

/* read parameters from a FileNode object and store them (struct function) */
void BinaryDescriptor::Params::read( const cv::FileNode& fn )
{
  numOfOctave_ = fn["numOfOctave_"];
  widthOfBand_ = fn["widthOfBand_"];
  reductionRatio = fn["reductionRatio"];
}

/* store parameters to a FileStorage object (struct function) */
void BinaryDescriptor::Params::write( cv::FileStorage& fs ) const
{
  fs << "numOfOctave_" << numOfOctave_;
  fs << "numOfBand_" << NUM_OF_BANDS;
  fs << "widthOfBand_" << widthOfBand_;
  fs << "reductionRatio" << reductionRatio;
}

Ptr<BinaryDescriptor> BinaryDescriptor::createBinaryDescriptor()
{
  return Ptr < BinaryDescriptor > ( new BinaryDescriptor() );
}

Ptr<BinaryDescriptor> BinaryDescriptor::createBinaryDescriptor( Params parameters )
{
  return Ptr < BinaryDescriptor > ( new BinaryDescriptor( parameters ) );
}

/* construct a BinaryDescrptor object and compute external private parameters */
BinaryDescriptor::BinaryDescriptor( const BinaryDescriptor::Params &parameters ) :
    params( parameters )
{
  /* reserve enough space for EDLine objects and images in Gaussian pyramid */
  edLineVec_.resize( params.numOfOctave_ );
  images_sizes.resize( params.numOfOctave_ );

  for ( int i = 0; i < params.numOfOctave_; i++ )
    edLineVec_[i] = Ptr < EDLineDetector > ( new EDLineDetector() );

  /* prepare a vector to host local weights F_l*/
  gaussCoefL_.resize( params.widthOfBand_ * 3 );

  /* compute center of central band (every computation involves 2-3 bands) */
  double u = ( params.widthOfBand_ * 3 - 1 ) / 2;

  /* compute exponential part of F_l */
  double sigma = ( params.widthOfBand_ * 2 + 1 ) / 2;  // (widthOfBand_*2+1)/2;
  double invsigma2 = -1 / ( 2 * sigma * sigma );

  /* compute all local weights */
  double dis;
  for ( int i = 0; i < params.widthOfBand_ * 3; i++ )
  {
    dis = i - u;
    gaussCoefL_[i] = exp( dis * dis * invsigma2 );
  }

  /* prepare a vector for global weights F_g*/
  gaussCoefG_.resize( NUM_OF_BANDS * params.widthOfBand_ );

  /* compute center of LSR */
  u = ( NUM_OF_BANDS * params.widthOfBand_ - 1 ) / 2;

  /* compute exponential part of F_g */
  sigma = u;
  invsigma2 = -1 / ( 2 * sigma * sigma );
  for ( int i = 0; i < NUM_OF_BANDS * params.widthOfBand_; i++ )
  {
    dis = i - u;
    gaussCoefG_[i] = exp( dis * dis * invsigma2 );
  }
}

/* definition of operator () */
void BinaryDescriptor::operator()( InputArray image, InputArray mask, CV_OUT std::vector<KeyLine>& keylines, OutputArray descriptors,
    bool useProvidedKeyLines, bool returnFloatDescr ) const
{

  /* create some matrix objects */
  cv::Mat imageMat, maskMat, descrMat;

  /* store reference to input matrices */
  imageMat = image.getMat();
  maskMat = mask.getMat();

  /* require drawing KeyLines detection if demanded */
  if( !useProvidedKeyLines )
  {
    keylines.clear();
    BinaryDescriptor *bn = const_cast<BinaryDescriptor*>( this );
    bn->edLineVec_.clear();
    bn->edLineVec_.resize( params.numOfOctave_ );

    for ( int i = 0; i < params.numOfOctave_; i++ )
    bn->edLineVec_[i] = Ptr<EDLineDetector>( new EDLineDetector() );

    detectImpl( imageMat, keylines, maskMat );

  }

  /* initialize output matrix */
  //descriptors.create( Size( 32, (int) keylines.size() ), CV_8UC1 );
  /* store reference to output matrix */
  //descrMat = descriptors.getMat();
  /* compute descriptors */
  if( !useProvidedKeyLines )
  computeImpl( imageMat, keylines, descrMat, returnFloatDescr, true );

  else
  computeImpl( imageMat, keylines, descrMat, returnFloatDescr, false );

  descrMat.copyTo( descriptors );
}

BinaryDescriptor::~BinaryDescriptor()
{

}

/* read parameters from a FileNode object and store them (class function ) */
void BinaryDescriptor::read( const cv::FileNode& fn )
{
  params.read( fn );
}

/* store parameters to a FileStorage object (class function) */
void BinaryDescriptor::write( cv::FileStorage& fs ) const
{
  params.write( fs );
}

/* return norm mode */
int BinaryDescriptor::defaultNorm() const
{
  return NORM_HAMMING;
}

/* return data type */
int BinaryDescriptor::descriptorType() const
{
  return CV_8U;
}

/*return descriptor size */
int BinaryDescriptor::descriptorSize() const
{
  return 32 * 8;
}

/* power function with error management */
static inline int get2Pow( int i )
{
  CV_DbgAssert(i >= 0 && i <= 7);
  return 1 << i;
}

/* compute Gaussian pyramids */
void BinaryDescriptor::computeGaussianPyramid( const Mat& image, const int numOctaves )
{
  /* clear class fields */
  images_sizes.clear();
  octaveImages.clear();

  /* insert input image into pyramid */
  cv::Mat currentMat = image.clone();
  cv::GaussianBlur( currentMat, currentMat, cv::Size( 5, 5 ), 1 );
  octaveImages.push_back( currentMat );
  images_sizes.push_back( currentMat.size() );

  /* fill Gaussian pyramid */
  for ( int pyrCounter = 1; pyrCounter < numOctaves; pyrCounter++ )
  {
    /* compute and store next image in pyramid and its size */
    pyrDown( currentMat, currentMat, Size( currentMat.cols / params.reductionRatio, currentMat.rows / params.reductionRatio ) );
    octaveImages.push_back( currentMat );
    images_sizes.push_back( currentMat.size() );
  }
}

/* compute Sobel's derivatives */
void BinaryDescriptor::computeSobel( const cv::Mat& image, const int numOctaves )
{

  /* compute Gaussian pyramids */
  computeGaussianPyramid( image, numOctaves );

  /* reinitialize class structures */
  dxImg_vector.clear();
  dyImg_vector.clear();

//  dxImg_vector.resize( params.numOfOctave_ );
//  dyImg_vector.resize( params.numOfOctave_ );

  dxImg_vector.resize( octaveImages.size() );
  dyImg_vector.resize( octaveImages.size() );

  /* compute derivatives */
  for ( size_t sobelCnt = 0; sobelCnt < octaveImages.size(); sobelCnt++ )
  {
    dxImg_vector[sobelCnt].create( images_sizes[sobelCnt].height, images_sizes[sobelCnt].width, CV_16SC1 );
    dyImg_vector[sobelCnt].create( images_sizes[sobelCnt].height, images_sizes[sobelCnt].width, CV_16SC1 );

    cv::Sobel( octaveImages[sobelCnt], dxImg_vector[sobelCnt], CV_16SC1, 1, 0, 3 );
    cv::Sobel( octaveImages[sobelCnt], dyImg_vector[sobelCnt], CV_16SC1, 0, 1, 3 );
  }
}

/* utility function for conversion of an LBD descriptor to its binary representation */
unsigned char BinaryDescriptor::binaryConversion( float* f1, float* f2 )
{
  uchar result = 0;
  for ( int i = 0; i < 8; i++ )
  {
    if( f1[i] > f2[i] )
      result += (uchar) get2Pow( i );
  }

  return result;

}

/* requires line detection (only one image) */
void BinaryDescriptor::detect( const Mat& image, CV_OUT std::vector<KeyLine>& keylines, const Mat& mask )
{
  if( image.data == NULL )
  {
    std::cout << "Error: input image for detection is empty" << std::endl;
    return;
  }

  if( mask.data != NULL && ( mask.size() != image.size() || mask.type() != CV_8UC1 ) )
    CV_Error( Error::StsBadArg, "Mask error while detecting lines: please check its dimensions and that data type is CV_8UC1" );

  else
  detectImpl( image, keylines, mask );
}

/* requires line detection (more than one image) */
void BinaryDescriptor::detect( const std::vector<Mat>& images, std::vector<std::vector<KeyLine> >& keylines, const std::vector<Mat>& masks ) const
{

  if( images.size() == 0 )
  {
    std::cout << "Error: input image for detection is empty" << std::endl;
    return;
  }

  /* detect lines from each image */
  for ( size_t counter = 0; counter < images.size(); counter++ )
  {
    if( masks[counter].data != NULL && ( masks[counter].size() != images[counter].size() || masks[counter].type() != CV_8UC1 ) )
      CV_Error( Error::StsBadArg, "Mask error while detecting lines: please check its dimensions and that data type is CV_8UC1" );

    else
      detectImpl( images[counter], keylines[counter], masks[counter] );
  }
}

void BinaryDescriptor::detectImpl( const Mat& imageSrc, std::vector<KeyLine>& keylines, const Mat& mask ) const
{

  cv::Mat image;
  if( imageSrc.channels() != 1 )
  {
    cvtColor( imageSrc, image, COLOR_BGR2GRAY );
  }
  else
    image = imageSrc.clone();

  /*check whether image depth is different from 0 */
  if( image.depth() != 0 )
    CV_Error( Error::BadDepth, "Warning, depth image!= 0" );

  /* create a pointer to self */
  BinaryDescriptor *bn = const_cast<BinaryDescriptor*>( this );

  /* detect and arrange lines across octaves */
  ScaleLines sl;
  bn->OctaveKeyLines( image, sl );

  /* fill KeyLines vector */
  for ( int i = 0; i < (int) sl.size(); i++ )
  {
    for ( size_t j = 0; j < sl[i].size(); j++ )
    {
      /* get current line */
      OctaveSingleLine osl = sl[i][j];

      /* create a KeyLine object */
      KeyLine kl;

      /* fill KeyLine's fields */
      kl.startPointX = osl.startPointX;  //extremes[0];
      kl.startPointY = osl.startPointY;  //extremes[1];
      kl.endPointX = osl.endPointX;  //extremes[2];
      kl.endPointY = osl.endPointY;  //extremes[3];
      kl.sPointInOctaveX = osl.sPointInOctaveX;
      kl.sPointInOctaveY = osl.sPointInOctaveY;
      kl.ePointInOctaveX = osl.ePointInOctaveX;
      kl.ePointInOctaveY = osl.ePointInOctaveY;
      kl.lineLength = osl.lineLength;
      kl.numOfPixels = osl.numOfPixels;

      kl.angle = osl.direction;
      kl.class_id = i;
      kl.octave = osl.octaveCount;
      kl.size = ( osl.endPointX - osl.startPointX ) * ( osl.endPointY - osl.startPointY );
      kl.response = osl.lineLength / max( images_sizes[osl.octaveCount].width, images_sizes[osl.octaveCount].height );
      kl.pt = Point2f( ( osl.endPointX + osl.startPointX ) / 2, ( osl.endPointY + osl.startPointY ) / 2 );

      /* store KeyLine */
      keylines.push_back( kl );
    }

  }

  /* delete undesired KeyLines, according to input mask */
  if( !mask.empty() )
  {
    for ( size_t keyCounter = 0; keyCounter < keylines.size(); )
    {
      KeyLine& kl = keylines[keyCounter];

      //due to imprecise floating point scaling in the pyramid a little overflow can occur in line coordinates,
      //especially on big images. It will be fixed here
      kl.startPointX = (float)std::min((int)kl.startPointX, mask.cols - 1);
      kl.startPointY = (float)std::min((int)kl.startPointY, mask.rows - 1);
      kl.endPointX = (float)std::min((int)kl.endPointX, mask.cols - 1);
      kl.endPointY = (float)std::min((int)kl.endPointY, mask.rows - 1);

      if( mask.at < uchar > ( (int) kl.startPointY, (int) kl.startPointX ) == 0 && mask.at < uchar > ( (int) kl.endPointY, (int) kl.endPointX ) == 0 )
        keylines.erase( keylines.begin() + keyCounter );
      else
        keyCounter++;
    }
  }

}

/* requires descriptors computation (only one image) */
void BinaryDescriptor::compute( const Mat& image, CV_OUT CV_IN_OUT std::vector<KeyLine>& keylines, CV_OUT Mat& descriptors,
    bool returnFloatDescr ) const
{
  computeImpl( image, keylines, descriptors, returnFloatDescr, false );
}

/* requires descriptors computation (more than one image) */
void BinaryDescriptor::compute( const std::vector<Mat>& images, std::vector<std::vector<KeyLine> >& keylines, std::vector<Mat>& descriptors,
                                bool returnFloatDescr ) const
{
  for ( size_t i = 0; i < images.size(); i++ )
    computeImpl( images[i], keylines[i], descriptors[i], returnFloatDescr, false );
}

/* implementation of descriptors computation */
void BinaryDescriptor::computeImpl( const Mat& imageSrc, std::vector<KeyLine>& keylines, Mat& descriptors, bool returnFloatDescr,
                                    bool useDetectionData ) const
{
  /* convert input image to gray scale */
  cv::Mat image;
  if( imageSrc.channels() != 1 )
    cvtColor( imageSrc, image, COLOR_BGR2GRAY );
  else
    image = imageSrc;

  /*check whether image's depth is different from 0 */
  if( image.depth() != 0 )
    CV_Error( Error::BadDepth, "Error, depth of image != 0" );

  /* keypoints list can't be empty */
  if( keylines.size() == 0 )
  {
    std::cout << "Error: keypoint list is empty" << std::endl;
    return;
  }

  BinaryDescriptor* bd = const_cast<BinaryDescriptor*>( this );

  /* get maximum class_id and octave*/
  int numLines = 0;
  int octaveIndex = -1;
  for ( size_t l = 0; l < keylines.size(); l++ )
  {
    if( keylines[l].class_id > numLines )
      numLines = keylines[l].class_id;

    if( keylines[l].octave > octaveIndex )
      octaveIndex = keylines[l].octave;
  }

  if( !useDetectionData )
    bd->computeSobel( image, octaveIndex + 1 );

  /* create a ScaleLines object */
  OctaveSingleLine fictiousOSL;
//  fictiousOSL.octaveCount = params.numOfOctave_ + 1;
//  LinesVec lv( params.numOfOctave_, fictiousOSL );
  fictiousOSL.octaveCount = octaveIndex + 1;
  LinesVec lv( octaveIndex + 1, fictiousOSL );
  ScaleLines sl( numLines + 1, lv );

  /* create a map to record association between KeyLines and their position
   in ScaleLines vector */
  std::map<std::pair<int, int>, size_t> correspondences;

  /* fill ScaleLines object */
  for ( size_t slCounter = 0; slCounter < keylines.size(); slCounter++ )
  {
    /* get a KeyLine object and create a new line */
    KeyLine kl = keylines[slCounter];
    OctaveSingleLine osl;

    /* insert data in newly created line */
    osl.startPointX = kl.startPointX;
    osl.startPointY = kl.startPointY;
    osl.endPointX = kl.endPointX;
    osl.endPointY = kl.endPointY;
    osl.sPointInOctaveX = kl.sPointInOctaveX;
    osl.sPointInOctaveY = kl.sPointInOctaveY;
    osl.ePointInOctaveX = kl.ePointInOctaveX;
    osl.ePointInOctaveY = kl.ePointInOctaveY;
    osl.lineLength = kl.lineLength;
    osl.numOfPixels = kl.numOfPixels;
    osl.salience = kl.response;

    osl.direction = kl.angle;
    osl.octaveCount = kl.octave;

    /* store new line */
    sl[kl.class_id][kl.octave] = osl;

    /* update map */
    int id = kl.class_id;
    int oct = kl.octave;
    correspondences.insert( std::pair<std::pair<int, int>, size_t>( std::pair<int, int>( id, oct ), slCounter ) );
  }

  /* delete useless OctaveSingleLines */
  for ( size_t i = 0; i < sl.size(); i++ )
  {
    for ( size_t j = 0; j < sl[i].size(); )
    {
      if( (int) ( sl[i][j] ).octaveCount > octaveIndex )
        ( sl[i] ).erase( ( sl[i] ).begin() + j );
      else j++;
    }
  }

  /* compute LBD descriptors */
  bd->computeLBD( sl, useDetectionData );

  /* resize output matrix */
  if( !returnFloatDescr )
    descriptors = cv::Mat( (int) keylines.size(), 32, CV_8UC1 );

  else
    descriptors = cv::Mat( (int) keylines.size(), NUM_OF_BANDS * 8, CV_32FC1 );

  /* fill output matrix with descriptors */
  for ( int k = 0; k < (int) sl.size(); k++ )
  {
    for ( int lineC = 0; lineC < (int) sl[k].size(); lineC++ )
    {
      /* get original index of keypoint */
      int lineOctave = ( sl[k][lineC] ).octaveCount;
      int originalIndex = (int)correspondences.find( std::pair<int, int>( k, lineOctave ) )->second;

      if( !returnFloatDescr )
      {
        /* get a pointer to correspondent row in output matrix */
        uchar* pointerToRow = descriptors.ptr( originalIndex );

        /* get LBD data */
        float* desVec = &sl[k][lineC].descriptor.front();

        /* fill current row with binary descriptor */
        for ( int comb = 0; comb < 32; comb++ )
        {
          *pointerToRow = bd->binaryConversion( &desVec[8 * combinations[comb][0]], &desVec[8 * combinations[comb][1]] );
          pointerToRow++;
        }
      }

      else
      {
        /* get a pointer to correspondent row in output matrix */
        float* pointerToRow = descriptors.ptr<float>( originalIndex );

        /* get LBD data */
        std::vector<float> desVec = sl[k][lineC].descriptor;

        for ( int count = 0; count < (int) desVec.size(); count++ )
        {
          *pointerToRow = desVec[count];
          pointerToRow++;
        }
      }

    }
  }

}

int BinaryDescriptor::OctaveKeyLines( cv::Mat& image, ScaleLines &keyLines )
{

  /* final number of extracted lines */
  unsigned int numOfFinalLine = 0;

  /* sigma values and reduction factor used in Gaussian pyramids */
  float preSigma2 = 0;  //orignal image is not blurred, has zero sigma;
  float curSigma2 = 1.0;  //[sqrt(2)]^0=1;
  double factor = sqrt( 2.0 );  //the down sample factor between connective two octave images

  /* loop over number of octaves */
  for ( int octaveCount = 0; octaveCount < params.numOfOctave_; octaveCount++ )
  {
    /* matrix storing results from blurring processes */
    cv::Mat blur;

    /* apply Gaussian blur */
    float increaseSigma = sqrt( curSigma2 - preSigma2 );
    cv::GaussianBlur( image, blur, cv::Size( params.ksize_, params.ksize_ ), increaseSigma );
    images_sizes[octaveCount] = blur.size();

    /* for current octave, extract lines */
    if( ( edLineVec_[octaveCount]->EDline( blur ) ) != 1 )
    {
      return -1;
    }

    /* update number of total extracted lines */
    numOfFinalLine += edLineVec_[octaveCount]->lines_.numOfLines;

    /* resize image for next level of pyramid */
    cv::resize( blur, image, cv::Size(), ( 1.f / factor ), ( 1.f / factor ), INTER_LINEAR_EXACT );

    /* update sigma values */
    preSigma2 = curSigma2;
    curSigma2 = curSigma2 * 2;

  } /* end of loop over number of octaves */

  /* prepare a vector to store octave information associated to extracted lines */
  std::vector < OctaveLine > octaveLines( numOfFinalLine );

  /* set lines' counter to 0 for reuse */
  numOfFinalLine = 0;

  /* counter to give a unique ID to lines in LineVecs */
  unsigned int lineIDInScaleLineVec = 0;

  /* floats to compute lines' lengths */
  float dx, dy;

  /* loop over lines extracted from scale 0 (original image) */
  for ( unsigned int lineCurId = 0; lineCurId < edLineVec_[0]->lines_.numOfLines; lineCurId++ )
  {
    /* FOR CURRENT LINE: */

    /* set octave from which it was extracted */
    octaveLines[numOfFinalLine].octaveCount = 0;
    /* set ID within its octave */
    octaveLines[numOfFinalLine].lineIDInOctave = lineCurId;
    /* set a unique ID among all lines extracted in all octaves */
    octaveLines[numOfFinalLine].lineIDInScaleLineVec = lineIDInScaleLineVec;

    /* compute absolute value of difference between X coordinates of line's extreme points */
    dx = fabs( edLineVec_[0]->lineEndpoints_[lineCurId][0] - edLineVec_[0]->lineEndpoints_[lineCurId][2] );
    /* compute absolute value of difference between Y coordinates of line's extreme points */
    dy = fabs( edLineVec_[0]->lineEndpoints_[lineCurId][1] - edLineVec_[0]->lineEndpoints_[lineCurId][3] );
    /* compute line's length */
    octaveLines[numOfFinalLine].lineLength = sqrt( dx * dx + dy * dy );

    /* update counters */
    numOfFinalLine++;
    lineIDInScaleLineVec++;
  }

  /* create and fill an array to store scale factors */
  float *scale = new float[params.numOfOctave_];
  scale[0] = 1;
  for ( int octaveCount = 1; octaveCount < params.numOfOctave_; octaveCount++ )
  {
    scale[octaveCount] = (float) ( factor * scale[octaveCount - 1] );
  }

  /* some variables' declarations */
  float rho1, rho2, tempValue;
  float direction, diffNear, length;
  unsigned int octaveID, lineIDInOctave;

  /*more than one octave image, organize lines in scale space.
   *lines corresponding to the same line in octave images should have the same index in the ScaleLineVec */
  if( params.numOfOctave_ > 1 )
  {
    /* some other variables' declarations */
    double twoPI = 2 * M_PI;
    unsigned int closeLineID = 0;
    float endPointDis, minEndPointDis, minLocalDis, maxLocalDis;
    float lp0, lp1, lp2, lp3, np0, np1, np2, np3;

    /* loop over list of octaves */
    for ( int octaveCount = 1; octaveCount < params.numOfOctave_; octaveCount++ )
    {
      /*for each line in current octave image, find their corresponding lines in the octaveLines,
       *give them the same value of lineIDInScaleLineVec*/

      /* loop over list of lines extracted from current octave */
      for ( unsigned int lineCurId = 0; lineCurId < edLineVec_[octaveCount]->lines_.numOfLines; lineCurId++ )
      {
        /* get (scaled) known term from equation of current line */
        rho1 = (float) ( scale[octaveCount] * fabs( edLineVec_[octaveCount]->lineEquations_[lineCurId][2] ) );

        /*nearThreshold depends on the distance of the image coordinate origin to current line.
         *so nearThreshold = rho1 * nearThresholdRatio, where nearThresholdRatio = 1-cos(10*pi/180) = 0.0152*/
        tempValue = (float) ( rho1 * 0.0152 );
        float diffNearThreshold = ( tempValue > 6 ) ? ( tempValue ) : 6;
        diffNearThreshold = ( diffNearThreshold < 12 ) ? diffNearThreshold : 12;

        /* compute scaled length of current line */
        dx = fabs( edLineVec_[octaveCount]->lineEndpoints_[lineCurId][0] - edLineVec_[octaveCount]->lineEndpoints_[lineCurId][2] );  //x1-x2
        dy = fabs( edLineVec_[octaveCount]->lineEndpoints_[lineCurId][1] - edLineVec_[octaveCount]->lineEndpoints_[lineCurId][3] );  //y1-y2
        length = scale[octaveCount] * sqrt( dx * dx + dy * dy );

        minEndPointDis = 12;
        /* loop over the octave representations of all lines */
        for ( unsigned int lineNextId = 0; lineNextId < numOfFinalLine; lineNextId++ )
        {
          /* if a line from same octave is encountered,
           a comparison with it shouldn't be considered */
          octaveID = octaveLines[lineNextId].octaveCount;
          if( (int) octaveID == octaveCount )
          {  //lines in the same layer of octave image should not be compared.
            break;
          }

          /* take ID in octave of line to be compared */
          lineIDInOctave = octaveLines[lineNextId].lineIDInOctave;

          /*first check whether current line and next line are parallel.
           *If line1:a1*x+b1*y+c1=0 and line2:a2*x+b2*y+c2=0 are parallel, then
           *-a1/b1=-a2/b2, i.e., a1b2=b1a2.
           *we define parallel=fabs(a1b2-b1a2)
           *note that, in EDLine class, we have normalized the line equations
           *to make a1^2+ b1^2 = a2^2+ b2^2 = 1*/
          direction = fabs( edLineVec_[octaveCount]->lineDirection_[lineCurId] - edLineVec_[octaveID]->lineDirection_[lineIDInOctave] );

          /* the angle between two lines are larger than 10degrees
           (i.e. 10*pi/180=0.1745), they are not close to parallel */
          if( direction > 0.1745 && ( twoPI - direction > 0.1745 ) )
          {
            continue;
          }
          /*now check whether current line and next line are near to each other.
           *If line1:a1*x+b1*y+c1=0 and line2:a2*x+b2*y+c2=0 are near in image, then
           *rho1 = |a1*0+b1*0+c1|/sqrt(a1^2+b1^2) and rho2 = |a2*0+b2*0+c2|/sqrt(a2^2+b2^2) should close.
           *In our case, rho1 = |c1| and rho2 = |c2|, because sqrt(a1^2+b1^2) = sqrt(a2^2+b2^2) = 1;
           *note that, lines are in different octave images, so we define near =  fabs(scale*rho1 - rho2) or
           *where scale is the scale factor between to octave images*/

          /* get known term from equation to be compared */
          rho2 = (float) ( scale[octaveID] * fabs( edLineVec_[octaveID]->lineEquations_[lineIDInOctave][2] ) );
          /* compute difference between known ters */
          diffNear = fabs( rho1 - rho2 );

          /* two lines are not close in the image */
          if( diffNear > diffNearThreshold )
          {
            continue;
          }

          /*now check the end points distance between two lines, the scale of  distance is in the original image size.
           * find the minimal and maximal end points distance*/

          /* get the extreme points of the two lines */
          lp0 = scale[octaveCount] * edLineVec_[octaveCount]->lineEndpoints_[lineCurId][0];
          lp1 = scale[octaveCount] * edLineVec_[octaveCount]->lineEndpoints_[lineCurId][1];
          lp2 = scale[octaveCount] * edLineVec_[octaveCount]->lineEndpoints_[lineCurId][2];
          lp3 = scale[octaveCount] * edLineVec_[octaveCount]->lineEndpoints_[lineCurId][3];
          np0 = scale[octaveID] * edLineVec_[octaveID]->lineEndpoints_[lineIDInOctave][0];
          np1 = scale[octaveID] * edLineVec_[octaveID]->lineEndpoints_[lineIDInOctave][1];
          np2 = scale[octaveID] * edLineVec_[octaveID]->lineEndpoints_[lineIDInOctave][2];
          np3 = scale[octaveID] * edLineVec_[octaveID]->lineEndpoints_[lineIDInOctave][3];

          /* get the distance between the two leftmost extremes of lines
           L1(0,1)<->L2(0,1) */
          dx = lp0 - np0;
          dy = lp1 - np1;
          endPointDis = sqrt( dx * dx + dy * dy );

          /* set momentaneously min and max distance between lines to
           the one between left extremes */
          minLocalDis = endPointDis;
          maxLocalDis = endPointDis;

          /* compute distance between right extremes
           L1(2,3)<->L2(2,3) */
          dx = lp2 - np2;
          dy = lp3 - np3;
          endPointDis = sqrt( dx * dx + dy * dy );

          /* update (if necessary) min and max distance between lines */
          minLocalDis = ( endPointDis < minLocalDis ) ? endPointDis : minLocalDis;
          maxLocalDis = ( endPointDis > maxLocalDis ) ? endPointDis : maxLocalDis;

          /* compute distance between left extreme of current line and
           right extreme of line to be compared
           L1(0,1)<->L2(2,3) */
          dx = lp0 - np2;
          dy = lp1 - np3;
          endPointDis = sqrt( dx * dx + dy * dy );

          /* update (if necessary) min and max distance between lines */
          minLocalDis = ( endPointDis < minLocalDis ) ? endPointDis : minLocalDis;
          maxLocalDis = ( endPointDis > maxLocalDis ) ? endPointDis : maxLocalDis;

          /* compute distance between right extreme of current line and
           left extreme of line to be compared
           L1(2,3)<->L2(0,1) */
          dx = lp2 - np0;
          dy = lp3 - np1;
          endPointDis = sqrt( dx * dx + dy * dy );

          /* update (if necessary) min and max distance between lines */
          minLocalDis = ( endPointDis < minLocalDis ) ? endPointDis : minLocalDis;
          maxLocalDis = ( endPointDis > maxLocalDis ) ? endPointDis : maxLocalDis;

          /* check whether conditions for considering line to be compared
           worth to be inserted in the same LineVec are satisfied */
          if( ( maxLocalDis < 0.8 * ( length + octaveLines[lineNextId].lineLength ) ) && ( minLocalDis < minEndPointDis ) )
          {  //keep the closest line
            minEndPointDis = minLocalDis;
            closeLineID = lineNextId;
          }
        }

        /* add current line into octaveLines */
        if( minEndPointDis < 12 )
        {
          octaveLines[numOfFinalLine].lineIDInScaleLineVec = octaveLines[closeLineID].lineIDInScaleLineVec;
        }
        else
        {
          octaveLines[numOfFinalLine].lineIDInScaleLineVec = lineIDInScaleLineVec;
          lineIDInScaleLineVec++;
        }
        octaveLines[numOfFinalLine].octaveCount = octaveCount;
        octaveLines[numOfFinalLine].lineIDInOctave = lineCurId;
        octaveLines[numOfFinalLine].lineLength = length;
        numOfFinalLine++;
      }
    }  //end for(unsigned int octaveCount = 1; octaveCount<numOfOctave_; octaveCount++)
  }  //end if(numOfOctave_>1)

  ////////////////////////////////////
  //Reorganize the detected lines into keyLines
  keyLines.clear();
  keyLines.resize( lineIDInScaleLineVec );
  unsigned int tempID;
  float s1, e1, s2, e2;
  bool shouldChange;
  OctaveSingleLine singleLine;
  for ( unsigned int lineID = 0; lineID < numOfFinalLine; lineID++ )
  {
    lineIDInOctave = octaveLines[lineID].lineIDInOctave;
    octaveID = octaveLines[lineID].octaveCount;
    direction = edLineVec_[octaveID]->lineDirection_[lineIDInOctave];
    singleLine.octaveCount = octaveID;
    singleLine.direction = direction;
    singleLine.lineLength = octaveLines[lineID].lineLength;
    singleLine.salience = edLineVec_[octaveID]->lineSalience_[lineIDInOctave];
    singleLine.numOfPixels = edLineVec_[octaveID]->lines_.sId[lineIDInOctave + 1] - edLineVec_[octaveID]->lines_.sId[lineIDInOctave];
    //decide the start point and end point
    shouldChange = false;
    s1 = edLineVec_[octaveID]->lineEndpoints_[lineIDInOctave][0];  //sx
    s2 = edLineVec_[octaveID]->lineEndpoints_[lineIDInOctave][1];  //sy
    e1 = edLineVec_[octaveID]->lineEndpoints_[lineIDInOctave][2];  //ex
    e2 = edLineVec_[octaveID]->lineEndpoints_[lineIDInOctave][3];  //ey
    dx = e1 - s1;  //ex-sx
    dy = e2 - s2;  //ey-sy
    if( direction >= -0.75 * M_PI && direction < -0.25 * M_PI )
    {
      if( dy > 0 )
      {
        shouldChange = true;
      }
    }
    if( direction >= -0.25 * M_PI && direction < 0.25 * M_PI )
    {
      if( dx < 0 )
      {
        shouldChange = true;
      }
    }
    if( direction >= 0.25 * M_PI && direction < 0.75 * M_PI )
    {
      if( dy < 0 )
      {
        shouldChange = true;
      }
    }
    if( ( direction >= 0.75 * M_PI && direction < M_PI ) || ( direction >= -M_PI && direction < -0.75 * M_PI ) )
    {
      if( dx > 0 )
      {
        shouldChange = true;
      }
    }
    tempValue = scale[octaveID];
    if( shouldChange )
    {
      singleLine.sPointInOctaveX = e1;
      singleLine.sPointInOctaveY = e2;
      singleLine.ePointInOctaveX = s1;
      singleLine.ePointInOctaveY = s2;
      singleLine.startPointX = tempValue * e1;
      singleLine.startPointY = tempValue * e2;
      singleLine.endPointX = tempValue * s1;
      singleLine.endPointY = tempValue * s2;
    }
    else
    {
      singleLine.sPointInOctaveX = s1;
      singleLine.sPointInOctaveY = s2;
      singleLine.ePointInOctaveX = e1;
      singleLine.ePointInOctaveY = e2;
      singleLine.startPointX = tempValue * s1;
      singleLine.startPointY = tempValue * s2;
      singleLine.endPointX = tempValue * e1;
      singleLine.endPointY = tempValue * e2;
    }
    tempID = octaveLines[lineID].lineIDInScaleLineVec;
    keyLines[tempID].push_back( singleLine );
  }

  delete[] scale;
  return 1;
}

int BinaryDescriptor::computeLBD( ScaleLines &keyLines, bool useDetectionData )
{
  //the default length of the band is the line length.
  short numOfFinalLine = (short) keyLines.size();
  float *dL = new float[2];  //line direction cos(dir), sin(dir)
  float *dO = new float[2];  //the clockwise orthogonal vector of line direction.
  short heightOfLSP = (short) ( params.widthOfBand_ * NUM_OF_BANDS );  //the height of line support region;
  short descriptor_size = NUM_OF_BANDS * 8;  //each band, we compute the m( pgdL, ngdL,  pgdO, ngdO) and std( pgdL, ngdL,  pgdO, ngdO);
  float pgdLRowSum;  //the summation of {g_dL |g_dL>0 } for each row of the region;
  float ngdLRowSum;  //the summation of {g_dL |g_dL<0 } for each row of the region;
  float pgdL2RowSum;  //the summation of {g_dL^2 |g_dL>0 } for each row of the region;
  float ngdL2RowSum;  //the summation of {g_dL^2 |g_dL<0 } for each row of the region;
  float pgdORowSum;  //the summation of {g_dO |g_dO>0 } for each row of the region;
  float ngdORowSum;  //the summation of {g_dO |g_dO<0 } for each row of the region;
  float pgdO2RowSum;  //the summation of {g_dO^2 |g_dO>0 } for each row of the region;
  float ngdO2RowSum;  //the summation of {g_dO^2 |g_dO<0 } for each row of the region;

  float *pgdLBandSum = new float[NUM_OF_BANDS];  //the summation of {g_dL |g_dL>0 } for each band of the region;
  float *ngdLBandSum = new float[NUM_OF_BANDS];  //the summation of {g_dL |g_dL<0 } for each band of the region;
  float *pgdL2BandSum = new float[NUM_OF_BANDS];  //the summation of {g_dL^2 |g_dL>0 } for each band of the region;
  float *ngdL2BandSum = new float[NUM_OF_BANDS];  //the summation of {g_dL^2 |g_dL<0 } for each band of the region;
  float *pgdOBandSum = new float[NUM_OF_BANDS];  //the summation of {g_dO |g_dO>0 } for each band of the region;
  float *ngdOBandSum = new float[NUM_OF_BANDS];  //the summation of {g_dO |g_dO<0 } for each band of the region;
  float *pgdO2BandSum = new float[NUM_OF_BANDS];  //the summation of {g_dO^2 |g_dO>0 } for each band of the region;
  float *ngdO2BandSum = new float[NUM_OF_BANDS];  //the summation of {g_dO^2 |g_dO<0 } for each band of the region;

  short numOfBitsBand = NUM_OF_BANDS * sizeof(float);
  short lengthOfLSP;  //the length of line support region, varies with lines
  short halfHeight = ( heightOfLSP - 1 ) / 2;
  short halfWidth;
  short bandID;
  float coefInGaussion;
  float lineMiddlePointX, lineMiddlePointY;
  float sCorX, sCorY, sCorX0, sCorY0;
  short tempCor, xCor, yCor;  //pixel coordinates in image plane
  short dx, dy;
  float gDL;  //store the gradient projection of pixels in support region along dL vector
  float gDO;  //store the gradient projection of pixels in support region along dO vector
  short imageWidth, imageHeight, realWidth;
  short *pdxImg, *pdyImg;
  float *desVec;

  short sameLineSize;
  short octaveCount;
  OctaveSingleLine *pSingleLine;
  /* loop over list of LineVec */
  for ( short lineIDInScaleVec = 0; lineIDInScaleVec < numOfFinalLine; lineIDInScaleVec++ )
  {
    sameLineSize = (short) ( keyLines[lineIDInScaleVec].size() );
    /* loop over current LineVec's lines */
    for ( short lineIDInSameLine = 0; lineIDInSameLine < sameLineSize; lineIDInSameLine++ )
    {
      /* get a line in current LineVec and its original ID in its octave */
      pSingleLine = & ( keyLines[lineIDInScaleVec][lineIDInSameLine] );
      octaveCount = (short) pSingleLine->octaveCount;

      if( useDetectionData )
      {
        /* retrieve associated dxImg and dyImg */
        pdxImg = edLineVec_[octaveCount]->dxImg_.ptr<short>();
        pdyImg = edLineVec_[octaveCount]->dyImg_.ptr<short>();

        /* get image size to work on from real one */
        realWidth = (short) edLineVec_[octaveCount]->imageWidth;
        imageWidth = realWidth - 1;
        imageHeight = (short) ( edLineVec_[octaveCount]->imageHeight - 1 );
      }

      else
      {
        /* retrieve associated dxImg and dyImg */
        pdxImg = dxImg_vector[octaveCount].ptr<short>();
        pdyImg = dyImg_vector[octaveCount].ptr<short>();

        /* get image size to work on from real one */
        realWidth = (short) images_sizes[octaveCount].width;
        imageWidth = realWidth - 1;
        imageHeight = (short) ( images_sizes[octaveCount].height - 1 );
      }

      /* initialize memory areas */
      memset( pgdLBandSum, 0, numOfBitsBand );
      memset( ngdLBandSum, 0, numOfBitsBand );
      memset( pgdL2BandSum, 0, numOfBitsBand );
      memset( ngdL2BandSum, 0, numOfBitsBand );
      memset( pgdOBandSum, 0, numOfBitsBand );
      memset( ngdOBandSum, 0, numOfBitsBand );
      memset( pgdO2BandSum, 0, numOfBitsBand );
      memset( ngdO2BandSum, 0, numOfBitsBand );

      /* get length of line and its half */
      lengthOfLSP = (short) keyLines[lineIDInScaleVec][lineIDInSameLine].numOfPixels;
      halfWidth = ( lengthOfLSP - 1 ) / 2;

      /* get middlepoint of line */
      lineMiddlePointX = (float) ( 0.5 * ( pSingleLine->sPointInOctaveX + pSingleLine->ePointInOctaveX ) );
      lineMiddlePointY = (float) ( 0.5 * ( pSingleLine->sPointInOctaveY + pSingleLine->ePointInOctaveY ) );

      /*1.rotate the local coordinate system to the line direction (direction is the angle
       between positive line direction and positive X axis)
       *2.compute the gradient projection of pixels in line support region*/

      /* get the vector representing original image reference system after rotation to aligh with
       line's direction */
      dL[0] = cos( pSingleLine->direction );
      dL[1] = sin( pSingleLine->direction );

      /* set the clockwise orthogonal vector of line direction */
      dO[0] = -dL[1];
      dO[1] = dL[0];

      /* get rotated reference frame */
      sCorX0 = -dL[0] * halfWidth + dL[1] * halfHeight + lineMiddlePointX;  //hID =0; wID = 0;
      sCorY0 = -dL[1] * halfWidth - dL[0] * halfHeight + lineMiddlePointY;

      /* BIAS::Matrix<float> gDLMat(heightOfLSP,lengthOfLSP) */
      for ( short hID = 0; hID < heightOfLSP; hID++ )
      {
        /*initialization */
        sCorX = sCorX0;
        sCorY = sCorY0;

        pgdLRowSum = 0;
        ngdLRowSum = 0;
        pgdORowSum = 0;
        ngdORowSum = 0;

        for ( short wID = 0; wID < lengthOfLSP; wID++ )
        {
          tempCor = (short) round( sCorX );
          xCor = ( tempCor < 0 ) ? 0 : ( tempCor > imageWidth ) ? imageWidth : tempCor;
          tempCor = (short) round( sCorY );
          yCor = ( tempCor < 0 ) ? 0 : ( tempCor > imageHeight ) ? imageHeight : tempCor;

          /* To achieve rotation invariance, each simple gradient is rotated aligned with
           * the line direction and clockwise orthogonal direction.*/
          dx = pdxImg[yCor * realWidth + xCor];
          dy = pdyImg[yCor * realWidth + xCor];
          gDL = dx * dL[0] + dy * dL[1];
          gDO = dx * dO[0] + dy * dO[1];
          if( gDL > 0 )
          {
            pgdLRowSum += gDL;
          }
          else
          {
            ngdLRowSum -= gDL;
          }
          if( gDO > 0 )
          {
            pgdORowSum += gDO;
          }
          else
          {
            ngdORowSum -= gDO;
          }
          sCorX += dL[0];
          sCorY += dL[1];
          /* gDLMat[hID][wID] = gDL; */
        }
        sCorX0 -= dL[1];
        sCorY0 += dL[0];
        coefInGaussion = (float) gaussCoefG_[hID];
        pgdLRowSum = coefInGaussion * pgdLRowSum;
        ngdLRowSum = coefInGaussion * ngdLRowSum;
        pgdL2RowSum = pgdLRowSum * pgdLRowSum;
        ngdL2RowSum = ngdLRowSum * ngdLRowSum;
        pgdORowSum = coefInGaussion * pgdORowSum;
        ngdORowSum = coefInGaussion * ngdORowSum;
        pgdO2RowSum = pgdORowSum * pgdORowSum;
        ngdO2RowSum = ngdORowSum * ngdORowSum;

        /* compute {g_dL |g_dL>0 }, {g_dL |g_dL<0 },
         {g_dO |g_dO>0 }, {g_dO |g_dO<0 } of each band in the line support region
         first, current row belong to current band */
        bandID = (short) ( hID / params.widthOfBand_ );
        coefInGaussion = (float) ( gaussCoefL_[hID % params.widthOfBand_ + params.widthOfBand_] );
        pgdLBandSum[bandID] += coefInGaussion * pgdLRowSum;
        ngdLBandSum[bandID] += coefInGaussion * ngdLRowSum;
        pgdL2BandSum[bandID] += coefInGaussion * coefInGaussion * pgdL2RowSum;
        ngdL2BandSum[bandID] += coefInGaussion * coefInGaussion * ngdL2RowSum;
        pgdOBandSum[bandID] += coefInGaussion * pgdORowSum;
        ngdOBandSum[bandID] += coefInGaussion * ngdORowSum;
        pgdO2BandSum[bandID] += coefInGaussion * coefInGaussion * pgdO2RowSum;
        ngdO2BandSum[bandID] += coefInGaussion * coefInGaussion * ngdO2RowSum;

        /* In order to reduce boundary effect along the line gradient direction,
         * a row's gradient will contribute not only to its current band, but also
         * to its nearest upper and down band with gaussCoefL_.*/
        bandID--;
        if( bandID >= 0 )
        {/* the band above the current band */
          coefInGaussion = (float) ( gaussCoefL_[hID % params.widthOfBand_ + 2 * params.widthOfBand_] );
          pgdLBandSum[bandID] += coefInGaussion * pgdLRowSum;
          ngdLBandSum[bandID] += coefInGaussion * ngdLRowSum;
          pgdL2BandSum[bandID] += coefInGaussion * coefInGaussion * pgdL2RowSum;
          ngdL2BandSum[bandID] += coefInGaussion * coefInGaussion * ngdL2RowSum;
          pgdOBandSum[bandID] += coefInGaussion * pgdORowSum;
          ngdOBandSum[bandID] += coefInGaussion * ngdORowSum;
          pgdO2BandSum[bandID] += coefInGaussion * coefInGaussion * pgdO2RowSum;
          ngdO2BandSum[bandID] += coefInGaussion * coefInGaussion * ngdO2RowSum;
        }
        bandID = bandID + 2;
        if( bandID < NUM_OF_BANDS )
        {/*the band below the current band */
          coefInGaussion = (float) ( gaussCoefL_[hID % params.widthOfBand_] );
          pgdLBandSum[bandID] += coefInGaussion * pgdLRowSum;
          ngdLBandSum[bandID] += coefInGaussion * ngdLRowSum;
          pgdL2BandSum[bandID] += coefInGaussion * coefInGaussion * pgdL2RowSum;
          ngdL2BandSum[bandID] += coefInGaussion * coefInGaussion * ngdL2RowSum;
          pgdOBandSum[bandID] += coefInGaussion * pgdORowSum;
          ngdOBandSum[bandID] += coefInGaussion * ngdORowSum;
          pgdO2BandSum[bandID] += coefInGaussion * coefInGaussion * pgdO2RowSum;
          ngdO2BandSum[bandID] += coefInGaussion * coefInGaussion * ngdO2RowSum;
        }
      }
      /* gDLMat.Save("gDLMat.txt");
       return 0; */

      /* construct line descriptor */
      pSingleLine->descriptor.resize( descriptor_size );
      desVec = &pSingleLine->descriptor.front();

      short desID;

      /*Note that the first and last bands only have (lengthOfLSP * widthOfBand_ * 2.0) pixels
       * which are counted. */
      float invN2 = (float) ( 1.0 / ( params.widthOfBand_ * 2.0 ) );
      float invN3 = (float) ( 1.0 / ( params.widthOfBand_ * 3.0 ) );
      float invN, temp;
      for ( bandID = 0; bandID < NUM_OF_BANDS; bandID++ )
      {
        if( bandID == 0 || bandID == NUM_OF_BANDS - 1 )
        {
          invN = invN2;
        }
        else
        {
          invN = invN3;
        }
        desID = bandID * 8;
        temp = pgdLBandSum[bandID] * invN;
        desVec[desID] = temp;/* mean value of pgdL; */
        desVec[desID + 4] = sqrt( pgdL2BandSum[bandID] * invN - temp * temp );  //std value of pgdL;
        temp = ngdLBandSum[bandID] * invN;
        desVec[desID + 1] = temp;  //mean value of ngdL;
        desVec[desID + 5] = sqrt( ngdL2BandSum[bandID] * invN - temp * temp );  //std value of ngdL;

        temp = pgdOBandSum[bandID] * invN;
        desVec[desID + 2] = temp;  //mean value of pgdO;
        desVec[desID + 6] = sqrt( pgdO2BandSum[bandID] * invN - temp * temp );  //std value of pgdO;
        temp = ngdOBandSum[bandID] * invN;
        desVec[desID + 3] = temp;  //mean value of ngdO;
        desVec[desID + 7] = sqrt( ngdO2BandSum[bandID] * invN - temp * temp );  //std value of ngdO;
      }

      // normalize;
      float tempM, tempS;
      tempM = 0;
      tempS = 0;
      desVec = &pSingleLine->descriptor.front();

      int base = 0;
      for ( short i = 0; i < (short) ( NUM_OF_BANDS * 8 ); ++base, i = (short) ( base * 8 ) )
      {
        tempM += * ( desVec + i ) * * ( desVec + i );  //desVec[8*i+0] * desVec[8*i+0];
        tempM += * ( desVec + i + 1 ) * * ( desVec + i + 1 );  //desVec[8*i+1] * desVec[8*i+1];
        tempM += * ( desVec + i + 2 ) * * ( desVec + i + 2 );  //desVec[8*i+2] * desVec[8*i+2];
        tempM += * ( desVec + i + 3 ) * * ( desVec + i + 3 );  //desVec[8*i+3] * desVec[8*i+3];
        tempS += * ( desVec + i + 4 ) * * ( desVec + i + 4 );  //desVec[8*i+4] * desVec[8*i+4];
        tempS += * ( desVec + i + 5 ) * * ( desVec + i + 5 );  //desVec[8*i+5] * desVec[8*i+5];
        tempS += * ( desVec + i + 6 ) * * ( desVec + i + 6 );  //desVec[8*i+6] * desVec[8*i+6];
        tempS += * ( desVec + i + 7 ) * * ( desVec + i + 7 );  //desVec[8*i+7] * desVec[8*i+7];
      }

      tempM = 1 / sqrt( tempM );
      tempS = 1 / sqrt( tempS );
      desVec = &pSingleLine->descriptor.front();
      base = 0;
      for ( short i = 0; i < (short) ( NUM_OF_BANDS * 8 ); ++base, i = (short) ( base * 8 ) )
      {
        * ( desVec + i ) = * ( desVec + i ) * tempM;  //desVec[8*i] =  desVec[8*i] * tempM;
        * ( desVec + 1 + i ) = * ( desVec + 1 + i ) * tempM;  //desVec[8*i+1] =  desVec[8*i+1] * tempM;
        * ( desVec + 2 + i ) = * ( desVec + 2 + i ) * tempM;  //desVec[8*i+2] =  desVec[8*i+2] * tempM;
        * ( desVec + 3 + i ) = * ( desVec + 3 + i ) * tempM;  //desVec[8*i+3] =  desVec[8*i+3] * tempM;
        * ( desVec + 4 + i ) = * ( desVec + 4 + i ) * tempS;  //desVec[8*i+4] =  desVec[8*i+4] * tempS;
        * ( desVec + 5 + i ) = * ( desVec + 5 + i ) * tempS;  //desVec[8*i+5] =  desVec[8*i+5] * tempS;
        * ( desVec + 6 + i ) = * ( desVec + 6 + i ) * tempS;  //desVec[8*i+6] =  desVec[8*i+6] * tempS;
        * ( desVec + 7 + i ) = * ( desVec + 7 + i ) * tempS;  //desVec[8*i+7] =  desVec[8*i+7] * tempS;
      }

      /* In order to reduce the influence of non-linear illumination,
       * a threshold is used to limit the value of element in the unit feature
       * vector no larger than this threshold. In Z.Wang's work, a value of 0.4 is found
       * empirically to be a proper threshold.*/
      desVec = &pSingleLine->descriptor.front();
      for ( short i = 0; i < descriptor_size; i++ )
      {
        if( desVec[i] > 0.4 )
        {
          desVec[i] = (float) 0.4;
        }
      }

      //re-normalize desVec;
      temp = 0;
      for ( short i = 0; i < descriptor_size; i++ )
      {
        temp += desVec[i] * desVec[i];
      }

      temp = 1 / sqrt( temp );
      for ( short i = 0; i < descriptor_size; i++ )
      {
        desVec[i] = desVec[i] * temp;
      }
    }/* end for(short lineIDInSameLine = 0; lineIDInSameLine<sameLineSize;
     lineIDInSameLine++) */

  }/* end for(short lineIDInScaleVec = 0;
   lineIDInScaleVec<numOfFinalLine; lineIDInScaleVec++) */

  delete[] dL;
  delete[] dO;
  delete[] pgdLBandSum;
  delete[] ngdLBandSum;
  delete[] pgdL2BandSum;
  delete[] ngdL2BandSum;
  delete[] pgdOBandSum;
  delete[] ngdOBandSum;
  delete[] pgdO2BandSum;
  delete[] ngdO2BandSum;

  return 1;

}

BinaryDescriptor::EDLineDetector::EDLineDetector()
{
  //set parameters for line segment detection
  ksize_ = 15;  //15
  sigma_ = 30.0;  //30
  gradienThreshold_ = 80;  // ***** ORIGINAL WAS 25
  anchorThreshold_ = 8;  //8
  scanIntervals_ = 2;  //2
  minLineLen_ = 15;  //15
  lineFitErrThreshold_ = 1.6;  //1.4
  InitEDLine_();
}
BinaryDescriptor::EDLineDetector::EDLineDetector( EDLineParam param )
{
  //set parameters for line segment detection
  ksize_ = param.ksize;
  sigma_ = param.sigma;
  gradienThreshold_ = (short) param.gradientThreshold;
  anchorThreshold_ = (unsigned char) param.anchorThreshold;
  scanIntervals_ = param.scanIntervals;
  minLineLen_ = param.minLineLen;
  lineFitErrThreshold_ = param.lineFitErrThreshold;
  InitEDLine_();
}
void BinaryDescriptor::EDLineDetector::InitEDLine_()
{
  bValidate_ = true;
  ATA = cv::Mat_<int>( 2, 2 );
  ATV = cv::Mat_<int>( 1, 2 );
  tempMatLineFit = cv::Mat_<int>( 2, 2 );
  tempVecLineFit = cv::Mat_<int>( 1, 2 );
  fitMatT = cv::Mat_<int>( 2, minLineLen_ );
  fitVec = cv::Mat_<int>( 1, minLineLen_ );
  for ( int i = 0; i < minLineLen_; i++ )
  {
    fitMatT[1][i] = 1;
  }
  dxImg_.create( 1, 1, CV_16SC1 );
  dyImg_.create( 1, 1, CV_16SC1 );
  gImgWO_.create( 1, 1, CV_8SC1 );
  pFirstPartEdgeX_ = NULL;
  pFirstPartEdgeY_ = NULL;
  pFirstPartEdgeS_ = NULL;
  pSecondPartEdgeX_ = NULL;
  pSecondPartEdgeY_ = NULL;
  pSecondPartEdgeS_ = NULL;
  pAnchorX_ = NULL;
  pAnchorY_ = NULL;
}

BinaryDescriptor::EDLineDetector::~EDLineDetector()
{
  if( pFirstPartEdgeX_ != NULL )
  {
    delete[] pFirstPartEdgeX_;
    delete[] pFirstPartEdgeY_;
    delete[] pSecondPartEdgeX_;
    delete[] pSecondPartEdgeY_;
    delete[] pAnchorX_;
    delete[] pAnchorY_;
  }
  if( pFirstPartEdgeS_ != NULL )
  {
    delete[] pFirstPartEdgeS_;
    delete[] pSecondPartEdgeS_;
  }
}

int BinaryDescriptor::EDLineDetector::EdgeDrawing( cv::Mat &image, EdgeChains &edgeChains )
{
  imageWidth = image.cols;
  imageHeight = image.rows;
  unsigned int pixelNum = imageWidth * imageHeight;

  unsigned int edgePixelArraySize = pixelNum / 5;
  unsigned int maxNumOfEdge = edgePixelArraySize / 20;
  //compute dx, dy images
  if( gImg_.cols != (int) imageWidth || gImg_.rows != (int) imageHeight )
  {
    if( pFirstPartEdgeX_ != NULL )
    {
      delete[] pFirstPartEdgeX_;
      delete[] pFirstPartEdgeY_;
      delete[] pSecondPartEdgeX_;
      delete[] pSecondPartEdgeY_;
      delete[] pFirstPartEdgeS_;
      delete[] pSecondPartEdgeS_;
      delete[] pAnchorX_;
      delete[] pAnchorY_;
    }

    dxImg_.create( imageHeight, imageWidth, CV_16SC1 );
    dyImg_.create( imageHeight, imageWidth, CV_16SC1 );
    gImgWO_.create( imageHeight, imageWidth, CV_16SC1 );
    gImg_.create( imageHeight, imageWidth, CV_16SC1 );
    dirImg_.create( imageHeight, imageWidth, CV_8UC1 );
    edgeImage_.create( imageHeight, imageWidth, CV_8UC1 );
    pFirstPartEdgeX_ = new unsigned int[edgePixelArraySize];
    pFirstPartEdgeY_ = new unsigned int[edgePixelArraySize];
    pSecondPartEdgeX_ = new unsigned int[edgePixelArraySize];
    pSecondPartEdgeY_ = new unsigned int[edgePixelArraySize];
    pFirstPartEdgeS_ = new unsigned int[maxNumOfEdge];
    pSecondPartEdgeS_ = new unsigned int[maxNumOfEdge];
    pAnchorX_ = new unsigned int[edgePixelArraySize];
    pAnchorY_ = new unsigned int[edgePixelArraySize];
  }
  cv::Sobel( image, dxImg_, CV_16SC1, 1, 0, 3 );
  cv::Sobel( image, dyImg_, CV_16SC1, 0, 1, 3 );

  //compute gradient and direction images
  cv::Mat dxABS_m = cv::abs( dxImg_ );
  cv::Mat dyABS_m = cv::abs( dyImg_ );
  cv::Mat sumDxDy;
  cv::add( dyABS_m, dxABS_m, sumDxDy );

  cv::threshold( sumDxDy, gImg_, gradienThreshold_ + 1, 255, cv::THRESH_TOZERO );
  gImg_ = gImg_ / 4;
  gImgWO_ = sumDxDy / 4;
  cv::compare( dxABS_m, dyABS_m, dirImg_, cv::CMP_LT );

  short *pgImg = gImg_.ptr<short>();
  unsigned char *pdirImg = dirImg_.ptr();

  //extract the anchors in the gradient image, store into a vector
  memset( pAnchorX_, 0, edgePixelArraySize * sizeof(unsigned int) );  //initialization
  memset( pAnchorY_, 0, edgePixelArraySize * sizeof(unsigned int) );
  unsigned int anchorsSize = 0;
  int indexInArray;
  unsigned char gValue1, gValue2, gValue3;
  for ( unsigned int w = 1; w < imageWidth - 1; w = w + scanIntervals_ )
  {
    for ( unsigned int h = 1; h < imageHeight - 1; h = h + scanIntervals_ )
    {
      indexInArray = h * imageWidth + w;
      //gValue1 = pdirImg[indexInArray];
      if( pdirImg[indexInArray] == Horizontal )
      {  //if the direction of pixel is horizontal, then compare with up and down
         //gValue2 = pgImg[indexInArray];
        if( pgImg[indexInArray] >= pgImg[indexInArray - imageWidth] + anchorThreshold_
            && pgImg[indexInArray] >= pgImg[indexInArray + imageWidth] + anchorThreshold_ )
        {       // (w,h) is accepted as an anchor
          pAnchorX_[anchorsSize] = w;
          pAnchorY_[anchorsSize++] = h;
        }
      }
      else
      {       // if(pdirImg[indexInArray]==Vertical){//it is vertical edge, should be compared with left and right
        //gValue2 = pgImg[indexInArray];
        if( pgImg[indexInArray] >= pgImg[indexInArray - 1] + anchorThreshold_ && pgImg[indexInArray] >= pgImg[indexInArray + 1] + anchorThreshold_ )
        {       // (w,h) is accepted as an anchor
          pAnchorX_[anchorsSize] = w;
          pAnchorY_[anchorsSize++] = h;
        }
      }
    }
  }
  if( anchorsSize > edgePixelArraySize )
  {
    std::cout << "anchor size is larger than its maximal size. anchorsSize=" << anchorsSize << ", maximal size = " << edgePixelArraySize << std::endl;
    return -1;
  }

  //link the anchors by smart routing
  edgeImage_.setTo( 0 );
  unsigned char *pEdgeImg = edgeImage_.data;
  memset( pFirstPartEdgeX_, 0, edgePixelArraySize * sizeof(unsigned int) );       //initialization
  memset( pFirstPartEdgeY_, 0, edgePixelArraySize * sizeof(unsigned int) );
  memset( pSecondPartEdgeX_, 0, edgePixelArraySize * sizeof(unsigned int) );
  memset( pSecondPartEdgeY_, 0, edgePixelArraySize * sizeof(unsigned int) );
  memset( pFirstPartEdgeS_, 0, maxNumOfEdge * sizeof(unsigned int) );
  memset( pSecondPartEdgeS_, 0, maxNumOfEdge * sizeof(unsigned int) );
  unsigned int offsetPFirst = 0, offsetPSecond = 0;
  unsigned int offsetPS = 0;

  unsigned int x, y;
  unsigned int lastX = 0;
  unsigned int lastY = 0;
  unsigned char lastDirection;        //up = 1, right = 2, down = 3, left = 4;
  unsigned char shouldGoDirection;        //up = 1, right = 2, down = 3, left = 4;
  int edgeLenFirst, edgeLenSecond;
  for ( unsigned int i = 0; i < anchorsSize; i++ )
  {
    x = pAnchorX_[i];
    y = pAnchorY_[i];
    indexInArray = y * imageWidth + x;
    if( pEdgeImg[indexInArray] )
    {       //if anchor i is already been an edge pixel.
      continue;
    }
    /*The walk stops under 3 conditions:
     * 1. We move out of the edge areas, i.e., the thresholded gradient value
     *    of the current pixel is 0.
     * 2. The current direction of the edge changes, i.e., from horizontal
     *    to vertical or vice versa.?? (This is turned out not correct. From the online edge draw demo
     *    we can figure out that authors don't implement this rule either because their extracted edge
     *    chain could be a circle which means pixel directions would definitely be different
     *    in somewhere on the chain.)
     * 3. We encounter a previously detected edge pixel. */
    pFirstPartEdgeS_[offsetPS] = offsetPFirst;
    if( pdirImg[indexInArray] == Horizontal )
    {       //if the direction of this pixel is horizontal, then go left and right.
      //fist go right, pixel direction may be different during linking.
      lastDirection = RightDir;
      while ( pgImg[indexInArray] > 0 && !pEdgeImg[indexInArray] )
      {
        pEdgeImg[indexInArray] = 1;        // Mark this pixel as an edge pixel
        pFirstPartEdgeX_[offsetPFirst] = x;
        pFirstPartEdgeY_[offsetPFirst++] = y;
        shouldGoDirection = 0;        //unknown
        if( pdirImg[indexInArray] == Horizontal )
        {        //should go left or right
          if( lastDirection == UpDir || lastDirection == DownDir )
          {        //change the pixel direction now
            if( x > lastX )
            {        //should go right
              shouldGoDirection = RightDir;
            }
            else
            {        //should go left
              shouldGoDirection = LeftDir;
            }
          }
          lastX = x;
          lastY = y;
          if( lastDirection == RightDir || shouldGoDirection == RightDir )
          {        //go right
            if( x == imageWidth - 1 || y == 0 || y == imageHeight - 1 )
            {        //reach the image border
              break;
            }
            // Look at 3 neighbors to the right and pick the one with the max. gradient value
            gValue1 = (unsigned char) pgImg[indexInArray - imageWidth + 1];
            gValue2 = (unsigned char) pgImg[indexInArray + 1];
            gValue3 = (unsigned char) pgImg[indexInArray + imageWidth + 1];
            if( gValue1 >= gValue2 && gValue1 >= gValue3 )
            {        //up-right
              x = x + 1;
              y = y - 1;
            }
            else if( gValue3 >= gValue2 && gValue3 >= gValue1 )
            {        //down-right
              x = x + 1;
              y = y + 1;
            }
            else
            {        //straight-right
              x = x + 1;
            }
            lastDirection = RightDir;
          }
          else if( lastDirection == LeftDir || shouldGoDirection == LeftDir )
          {        //go left
            if( x == 0 || y == 0 || y == imageHeight - 1 )
            {        //reach the image border
              break;
            }
            // Look at 3 neighbors to the left and pick the one with the max. gradient value
            gValue1 = (unsigned char) pgImg[indexInArray - imageWidth - 1];
            gValue2 = (unsigned char) pgImg[indexInArray - 1];
            gValue3 = (unsigned char) pgImg[indexInArray + imageWidth - 1];
            if( gValue1 >= gValue2 && gValue1 >= gValue3 )
            {        //up-left
              x = x - 1;
              y = y - 1;
            }
            else if( gValue3 >= gValue2 && gValue3 >= gValue1 )
            {        //down-left
              x = x - 1;
              y = y + 1;
            }
            else
            {        //straight-left
              x = x - 1;
            }
            lastDirection = LeftDir;
          }
        }
        else
        {        //should go up or down.
          if( lastDirection == RightDir || lastDirection == LeftDir )
          {        //change the pixel direction now
            if( y > lastY )
            {        //should go down
              shouldGoDirection = DownDir;
            }
            else
            {        //should go up
              shouldGoDirection = UpDir;
            }
          }
          lastX = x;
          lastY = y;
          if( lastDirection == DownDir || shouldGoDirection == DownDir )
          {        //go down
            if( x == 0 || x == imageWidth - 1 || y == imageHeight - 1 )
            {        //reach the image border
              break;
            }
            // Look at 3 neighbors to the down and pick the one with the max. gradient value
            gValue1 = (unsigned char) pgImg[indexInArray + imageWidth + 1];
            gValue2 = (unsigned char) pgImg[indexInArray + imageWidth];
            gValue3 = (unsigned char) pgImg[indexInArray + imageWidth - 1];
            if( gValue1 >= gValue2 && gValue1 >= gValue3 )
            {        //down-right
              x = x + 1;
              y = y + 1;
            }
            else if( gValue3 >= gValue2 && gValue3 >= gValue1 )
            {        //down-left
              x = x - 1;
              y = y + 1;
            }
            else
            {        //straight-down
              y = y + 1;
            }
            lastDirection = DownDir;
          }
          else if( lastDirection == UpDir || shouldGoDirection == UpDir )
          {        //go up
            if( x == 0 || x == imageWidth - 1 || y == 0 )
            {        //reach the image border
              break;
            }
            // Look at 3 neighbors to the up and pick the one with the max. gradient value
            gValue1 = (unsigned char) pgImg[indexInArray - imageWidth + 1];
            gValue2 = (unsigned char) pgImg[indexInArray - imageWidth];
            gValue3 = (unsigned char) pgImg[indexInArray - imageWidth - 1];
            if( gValue1 >= gValue2 && gValue1 >= gValue3 )
            {        //up-right
              x = x + 1;
              y = y - 1;
            }
            else if( gValue3 >= gValue2 && gValue3 >= gValue1 )
            {        //up-left
              x = x - 1;
              y = y - 1;
            }
            else
            {        //straight-up
              y = y - 1;
            }
            lastDirection = UpDir;
          }
        }
        indexInArray = y * imageWidth + x;
      }        //end while go right
               //then go left, pixel direction may be different during linking.
      x = pAnchorX_[i];
      y = pAnchorY_[i];
      indexInArray = y * imageWidth + x;
      pEdgeImg[indexInArray] = 0;     //mark the anchor point be a non-edge pixel and
      lastDirection = LeftDir;
      pSecondPartEdgeS_[offsetPS] = offsetPSecond;
      while ( pgImg[indexInArray] > 0 && !pEdgeImg[indexInArray] )
      {
        pEdgeImg[indexInArray] = 1;        // Mark this pixel as an edge pixel
        pSecondPartEdgeX_[offsetPSecond] = x;
        pSecondPartEdgeY_[offsetPSecond++] = y;
        shouldGoDirection = 0;        //unknown
        if( pdirImg[indexInArray] == Horizontal )
        {        //should go left or right
          if( lastDirection == UpDir || lastDirection == DownDir )
          {        //change the pixel direction now
            if( x > lastX )
            {        //should go right
              shouldGoDirection = RightDir;
            }
            else
            {        //should go left
              shouldGoDirection = LeftDir;
            }
          }
          lastX = x;
          lastY = y;
          if( lastDirection == RightDir || shouldGoDirection == RightDir )
          {        //go right
            if( x == imageWidth - 1 || y == 0 || y == imageHeight - 1 )
            {        //reach the image border
              break;
            }
            // Look at 3 neighbors to the right and pick the one with the max. gradient value
            gValue1 = (unsigned char) pgImg[indexInArray - imageWidth + 1];
            gValue2 = (unsigned char) pgImg[indexInArray + 1];
            gValue3 = (unsigned char) pgImg[indexInArray + imageWidth + 1];
            if( gValue1 >= gValue2 && gValue1 >= gValue3 )
            {        //up-right
              x = x + 1;
              y = y - 1;
            }
            else if( gValue3 >= gValue2 && gValue3 >= gValue1 )
            {        //down-right
              x = x + 1;
              y = y + 1;
            }
            else
            {        //straight-right
              x = x + 1;
            }
            lastDirection = RightDir;
          }
          else if( lastDirection == LeftDir || shouldGoDirection == LeftDir )
          {        //go left
            if( x == 0 || y == 0 || y == imageHeight - 1 )
            {        //reach the image border
              break;
            }
            // Look at 3 neighbors to the left and pick the one with the max. gradient value
            gValue1 = (unsigned char) pgImg[indexInArray - imageWidth - 1];
            gValue2 = (unsigned char) pgImg[indexInArray - 1];
            gValue3 = (unsigned char) pgImg[indexInArray + imageWidth - 1];
            if( gValue1 >= gValue2 && gValue1 >= gValue3 )
            {        //up-left
              x = x - 1;
              y = y - 1;
            }
            else if( gValue3 >= gValue2 && gValue3 >= gValue1 )
            {        //down-left
              x = x - 1;
              y = y + 1;
            }
            else
            {        //straight-left
              x = x - 1;
            }
            lastDirection = LeftDir;
          }
        }
        else
        {        //should go up or down.
          if( lastDirection == RightDir || lastDirection == LeftDir )
          {        //change the pixel direction now
            if( y > lastY )
            {        //should go down
              shouldGoDirection = DownDir;
            }
            else
            {        //should go up
              shouldGoDirection = UpDir;
            }
          }
          lastX = x;
          lastY = y;
          if( lastDirection == DownDir || shouldGoDirection == DownDir )
          {        //go down
            if( x == 0 || x == imageWidth - 1 || y == imageHeight - 1 )
            {        //reach the image border
              break;
            }
            // Look at 3 neighbors to the down and pick the one with the max. gradient value
            gValue1 = (unsigned char) pgImg[indexInArray + imageWidth + 1];
            gValue2 = (unsigned char) pgImg[indexInArray + imageWidth];
            gValue3 = (unsigned char) pgImg[indexInArray + imageWidth - 1];
            if( gValue1 >= gValue2 && gValue1 >= gValue3 )
            {        //down-right
              x = x + 1;
              y = y + 1;
            }
            else if( gValue3 >= gValue2 && gValue3 >= gValue1 )
            {        //down-left
              x = x - 1;
              y = y + 1;
            }
            else
            {        //straight-down
              y = y + 1;
            }
            lastDirection = DownDir;
          }
          else if( lastDirection == UpDir || shouldGoDirection == UpDir )
          {        //go up
            if( x == 0 || x == imageWidth - 1 || y == 0 )
            {        //reach the image border
              break;
            }
            // Look at 3 neighbors to the up and pick the one with the max. gradient value
            gValue1 = (unsigned char) pgImg[indexInArray - imageWidth + 1];
            gValue2 = (unsigned char) pgImg[indexInArray - imageWidth];
            gValue3 = (unsigned char) pgImg[indexInArray - imageWidth - 1];
            if( gValue1 >= gValue2 && gValue1 >= gValue3 )
            {        //up-right
              x = x + 1;
              y = y - 1;
            }
            else if( gValue3 >= gValue2 && gValue3 >= gValue1 )
            {        //up-left
              x = x - 1;
              y = y - 1;
            }
            else
            {        //straight-up
              y = y - 1;
            }
            lastDirection = UpDir;
          }
        }
        indexInArray = y * imageWidth + x;
      }        //end while go left
               //end anchor is Horizontal
    }
    else
    {     //the direction of this pixel is vertical, go up and down
      //fist go down, pixel direction may be different during linking.
      lastDirection = DownDir;
      while ( pgImg[indexInArray] > 0 && !pEdgeImg[indexInArray] )
      {
        pEdgeImg[indexInArray] = 1;        // Mark this pixel as an edge pixel
        pFirstPartEdgeX_[offsetPFirst] = x;
        pFirstPartEdgeY_[offsetPFirst++] = y;
        shouldGoDirection = 0;        //unknown
        if( pdirImg[indexInArray] == Horizontal )
        {        //should go left or right
          if( lastDirection == UpDir || lastDirection == DownDir )
          {        //change the pixel direction now
            if( x > lastX )
            {        //should go right
              shouldGoDirection = RightDir;
            }
            else
            {        //should go left
              shouldGoDirection = LeftDir;
            }
          }
          lastX = x;
          lastY = y;
          if( lastDirection == RightDir || shouldGoDirection == RightDir )
          {        //go right
            if( x == imageWidth - 1 || y == 0 || y == imageHeight - 1 )
            {        //reach the image border
              break;
            }
            // Look at 3 neighbors to the right and pick the one with the max. gradient value
            gValue1 = (unsigned char) pgImg[indexInArray - imageWidth + 1];
            gValue2 = (unsigned char) pgImg[indexInArray + 1];
            gValue3 = (unsigned char) pgImg[indexInArray + imageWidth + 1];
            if( gValue1 >= gValue2 && gValue1 >= gValue3 )
            {        //up-right
              x = x + 1;
              y = y - 1;
            }
            else if( gValue3 >= gValue2 && gValue3 >= gValue1 )
            {        //down-right
              x = x + 1;
              y = y + 1;
            }
            else
            {        //straight-right
              x = x + 1;
            }
            lastDirection = RightDir;
          }
          else if( lastDirection == LeftDir || shouldGoDirection == LeftDir )
          {        //go left
            if( x == 0 || y == 0 || y == imageHeight - 1 )
            {        //reach the image border
              break;
            }
            // Look at 3 neighbors to the left and pick the one with the max. gradient value
            gValue1 = (unsigned char) pgImg[indexInArray - imageWidth - 1];
            gValue2 = (unsigned char) pgImg[indexInArray - 1];
            gValue3 = (unsigned char) pgImg[indexInArray + imageWidth - 1];
            if( gValue1 >= gValue2 && gValue1 >= gValue3 )
            {        //up-left
              x = x - 1;
              y = y - 1;
            }
            else if( gValue3 >= gValue2 && gValue3 >= gValue1 )
            {        //down-left
              x = x - 1;
              y = y + 1;
            }
            else
            {        //straight-left
              x = x - 1;
            }
            lastDirection = LeftDir;
          }
        }
        else
        {        //should go up or down.
          if( lastDirection == RightDir || lastDirection == LeftDir )
          {        //change the pixel direction now
            if( y > lastY )
            {        //should go down
              shouldGoDirection = DownDir;
            }
            else
            {        //should go up
              shouldGoDirection = UpDir;
            }
          }
          lastX = x;
          lastY = y;
          if( lastDirection == DownDir || shouldGoDirection == DownDir )
          {        //go down
            if( x == 0 || x == imageWidth - 1 || y == imageHeight - 1 )
            {        //reach the image border
              break;
            }
            // Look at 3 neighbors to the down and pick the one with the max. gradient value
            gValue1 = (unsigned char) pgImg[indexInArray + imageWidth + 1];
            gValue2 = (unsigned char) pgImg[indexInArray + imageWidth];
            gValue3 = (unsigned char) pgImg[indexInArray + imageWidth - 1];
            if( gValue1 >= gValue2 && gValue1 >= gValue3 )
            {        //down-right
              x = x + 1;
              y = y + 1;
            }
            else if( gValue3 >= gValue2 && gValue3 >= gValue1 )
            {        //down-left
              x = x - 1;
              y = y + 1;
            }
            else
            {        //straight-down
              y = y + 1;
            }
            lastDirection = DownDir;
          }
          else if( lastDirection == UpDir || shouldGoDirection == UpDir )
          {        //go up
            if( x == 0 || x == imageWidth - 1 || y == 0 )
            {        //reach the image border
              break;
            }
            // Look at 3 neighbors to the up and pick the one with the max. gradient value
            gValue1 = (unsigned char) pgImg[indexInArray - imageWidth + 1];
            gValue2 = (unsigned char) pgImg[indexInArray - imageWidth];
            gValue3 = (unsigned char) pgImg[indexInArray - imageWidth - 1];
            if( gValue1 >= gValue2 && gValue1 >= gValue3 )
            {        //up-right
              x = x + 1;
              y = y - 1;
            }
            else if( gValue3 >= gValue2 && gValue3 >= gValue1 )
            {        //up-left
              x = x - 1;
              y = y - 1;
            }
            else
            {        //straight-up
              y = y - 1;
            }
            lastDirection = UpDir;
          }
        }
        indexInArray = y * imageWidth + x;
      }        //end while go down
               //then go up, pixel direction may be different during linking.
      lastDirection = UpDir;
      x = pAnchorX_[i];
      y = pAnchorY_[i];
      indexInArray = y * imageWidth + x;
      pEdgeImg[indexInArray] = 0;     //mark the anchor point be a non-edge pixel and
      pSecondPartEdgeS_[offsetPS] = offsetPSecond;
      while ( pgImg[indexInArray] > 0 && !pEdgeImg[indexInArray] )
      {
        pEdgeImg[indexInArray] = 1;        // Mark this pixel as an edge pixel
        pSecondPartEdgeX_[offsetPSecond] = x;
        pSecondPartEdgeY_[offsetPSecond++] = y;
        shouldGoDirection = 0;        //unknown
        if( pdirImg[indexInArray] == Horizontal )
        {        //should go left or right
          if( lastDirection == UpDir || lastDirection == DownDir )
          {        //change the pixel direction now
            if( x > lastX )
            {        //should go right
              shouldGoDirection = RightDir;
            }
            else
            {        //should go left
              shouldGoDirection = LeftDir;
            }
          }
          lastX = x;
          lastY = y;
          if( lastDirection == RightDir || shouldGoDirection == RightDir )
          {        //go right
            if( x == imageWidth - 1 || y == 0 || y == imageHeight - 1 )
            {        //reach the image border
              break;
            }
            // Look at 3 neighbors to the right and pick the one with the max. gradient value
            gValue1 = (unsigned char) pgImg[indexInArray - imageWidth + 1];
            gValue2 = (unsigned char) pgImg[indexInArray + 1];
            gValue3 = (unsigned char) pgImg[indexInArray + imageWidth + 1];
            if( gValue1 >= gValue2 && gValue1 >= gValue3 )
            {        //up-right
              x = x + 1;
              y = y - 1;
            }
            else if( gValue3 >= gValue2 && gValue3 >= gValue1 )
            {        //down-right
              x = x + 1;
              y = y + 1;
            }
            else
            {        //straight-right
              x = x + 1;
            }
            lastDirection = RightDir;
          }
          else if( lastDirection == LeftDir || shouldGoDirection == LeftDir )
          {        //go left
            if( x == 0 || y == 0 || y == imageHeight - 1 )
            {        //reach the image border
              break;
            }
            // Look at 3 neighbors to the left and pick the one with the max. gradient value
            gValue1 = (unsigned char) pgImg[indexInArray - imageWidth - 1];
            gValue2 = (unsigned char) pgImg[indexInArray - 1];
            gValue3 = (unsigned char) pgImg[indexInArray + imageWidth - 1];
            if( gValue1 >= gValue2 && gValue1 >= gValue3 )
            {        //up-left
              x = x - 1;
              y = y - 1;
            }
            else if( gValue3 >= gValue2 && gValue3 >= gValue1 )
            {        //down-left
              x = x - 1;
              y = y + 1;
            }
            else
            {        //straight-left
              x = x - 1;
            }
            lastDirection = LeftDir;
          }
        }
        else
        {        //should go up or down.
          if( lastDirection == RightDir || lastDirection == LeftDir )
          {        //change the pixel direction now
            if( y > lastY )
            {        //should go down
              shouldGoDirection = DownDir;
            }
            else
            {        //should go up
              shouldGoDirection = UpDir;
            }
          }
          lastX = x;
          lastY = y;
          if( lastDirection == DownDir || shouldGoDirection == DownDir )
          {        //go down
            if( x == 0 || x == imageWidth - 1 || y == imageHeight - 1 )
            {        //reach the image border
              break;
            }
            // Look at 3 neighbors to the down and pick the one with the max. gradient value
            gValue1 = (unsigned char) pgImg[indexInArray + imageWidth + 1];
            gValue2 = (unsigned char) pgImg[indexInArray + imageWidth];
            gValue3 = (unsigned char) pgImg[indexInArray + imageWidth - 1];
            if( gValue1 >= gValue2 && gValue1 >= gValue3 )
            {        //down-right
              x = x + 1;
              y = y + 1;
            }
            else if( gValue3 >= gValue2 && gValue3 >= gValue1 )
            {        //down-left
              x = x - 1;
              y = y + 1;
            }
            else
            {        //straight-down
              y = y + 1;
            }
            lastDirection = DownDir;
          }
          else if( lastDirection == UpDir || shouldGoDirection == UpDir )
          {        //go up
            if( x == 0 || x == imageWidth - 1 || y == 0 )
            {        //reach the image border
              break;
            }
            // Look at 3 neighbors to the up and pick the one with the max. gradient value
            gValue1 = (unsigned char) pgImg[indexInArray - imageWidth + 1];
            gValue2 = (unsigned char) pgImg[indexInArray - imageWidth];
            gValue3 = (unsigned char) pgImg[indexInArray - imageWidth - 1];
            if( gValue1 >= gValue2 && gValue1 >= gValue3 )
            {        //up-right
              x = x + 1;
              y = y - 1;
            }
            else if( gValue3 >= gValue2 && gValue3 >= gValue1 )
            {        //up-left
              x = x - 1;
              y = y - 1;
            }
            else
            {        //straight-up
              y = y - 1;
            }
            lastDirection = UpDir;
          }
        }
        indexInArray = y * imageWidth + x;
      }        //end while go up
    }        //end anchor is Vertical
             //only keep the edge chains whose length is larger than the minLineLen_;
    edgeLenFirst = offsetPFirst - pFirstPartEdgeS_[offsetPS];
    edgeLenSecond = offsetPSecond - pSecondPartEdgeS_[offsetPS];
    if( edgeLenFirst + edgeLenSecond < minLineLen_ + 1 )
    {   //short edge, drop it
      offsetPFirst = pFirstPartEdgeS_[offsetPS];
      offsetPSecond = pSecondPartEdgeS_[offsetPS];
    }
    else
    {
      offsetPS++;
    }
  }
  //store the last index
  pFirstPartEdgeS_[offsetPS] = offsetPFirst;
  pSecondPartEdgeS_[offsetPS] = offsetPSecond;
  if( offsetPS > maxNumOfEdge )
  {
    std::cout << "Edge drawing Error: The total number of edges is larger than MaxNumOfEdge, "
        "numofedge = " << offsetPS << ", MaxNumOfEdge=" << maxNumOfEdge << std::endl;
    return -1;
  }
  if( offsetPFirst > edgePixelArraySize || offsetPSecond > edgePixelArraySize )
  {
    std::cout << "Edge drawing Error: The total number of edge pixels is larger than MaxNumOfEdgePixels, "
        "numofedgePixel1 = " << offsetPFirst << ",  numofedgePixel2 = " << offsetPSecond << ", MaxNumOfEdgePixel=" << edgePixelArraySize << std::endl;
    return -1;
  }
  if( !(offsetPFirst && offsetPSecond) )
  {
      std::cout << "Edge drawing Error: lines not found" << std::endl;
      return -1;
  }

  /*now all the edge information are stored in pFirstPartEdgeX_, pFirstPartEdgeY_,
   *pFirstPartEdgeS_,  pSecondPartEdgeX_, pSecondPartEdgeY_, pSecondPartEdgeS_;
   *we should reorganize them into edgeChains for easily using. */
  int tempID;
  edgeChains.xCors.resize( offsetPFirst + offsetPSecond );
  edgeChains.yCors.resize( offsetPFirst + offsetPSecond );
  edgeChains.sId.resize( offsetPS + 1 );
  unsigned int *pxCors = &edgeChains.xCors.front();
  unsigned int *pyCors = &edgeChains.yCors.front();
  unsigned int *psId = &edgeChains.sId.front();
  offsetPFirst = 0;
  offsetPSecond = 0;
  unsigned int indexInCors = 0;
  unsigned int numOfEdges = 0;
  for ( unsigned int edgeId = 0; edgeId < offsetPS; edgeId++ )
  {
    //step1, put the first and second parts edge coordinates together from edge start to edge end
    psId[numOfEdges++] = indexInCors;
    indexInArray = pFirstPartEdgeS_[edgeId];
    offsetPFirst = pFirstPartEdgeS_[edgeId + 1];
    for ( tempID = offsetPFirst - 1; tempID >= indexInArray; tempID-- )
    {   //add first part edge
      pxCors[indexInCors] = pFirstPartEdgeX_[tempID];
      pyCors[indexInCors++] = pFirstPartEdgeY_[tempID];
    }
    indexInArray = pSecondPartEdgeS_[edgeId];
    offsetPSecond = pSecondPartEdgeS_[edgeId + 1];
    for ( tempID = indexInArray + 1; tempID < (int) offsetPSecond; tempID++ )
    {   //add second part edge
      pxCors[indexInCors] = pSecondPartEdgeX_[tempID];
      pyCors[indexInCors++] = pSecondPartEdgeY_[tempID];
    }
  }
  psId[numOfEdges] = indexInCors;   //the end index of the last edge
  edgeChains.numOfEdges = numOfEdges;

  return 1;
}

int BinaryDescriptor::EDLineDetector::EDline( cv::Mat &image, LineChains &lines )
{

  //first, call EdgeDrawing function to extract edges
  EdgeChains edges;
  if( ( EdgeDrawing( image, edges ) ) != 1 )
  {
    std::cout << "Line Detection not finished" << std::endl;
    return -1;
  }

  //detect lines
  unsigned int linePixelID = edges.sId[edges.numOfEdges];
  lines.xCors.resize( linePixelID );
  lines.yCors.resize( linePixelID );
  lines.sId.resize( 5 * edges.numOfEdges );
  unsigned int *pEdgeXCors = &edges.xCors.front();
  unsigned int *pEdgeYCors = &edges.yCors.front();
  unsigned int *pEdgeSID = &edges.sId.front();
  unsigned int *pLineXCors = &lines.xCors.front();
  unsigned int *pLineYCors = &lines.yCors.front();
  unsigned int *pLineSID = &lines.sId.front();
  logNT_ = 2.0 * ( log10( (double) imageWidth ) + log10( (double) imageHeight ) );
  double lineFitErr = 0;    //the line fit error;
  std::vector<double> lineEquation( 2, 0 );
  lineEquations_.clear();
  lineEndpoints_.clear();
  lineDirection_.clear();
  unsigned char *pdirImg = dirImg_.data;
  unsigned int numOfLines = 0;
  unsigned int newOffsetS = 0;
  unsigned int offsetInEdgeArrayS, offsetInEdgeArrayE;    //start index and end index
  unsigned int offsetInLineArray = 0;
  float direction;    //line direction

  for ( unsigned int edgeID = 0; edgeID < edges.numOfEdges; edgeID++ )
  {
    offsetInEdgeArrayS = pEdgeSID[edgeID];
    offsetInEdgeArrayE = pEdgeSID[edgeID + 1];
    while ( offsetInEdgeArrayE > offsetInEdgeArrayS + minLineLen_ )
    {   //extract line segments from an edge, may find more than one segments
      //find an initial line segment
      while ( offsetInEdgeArrayE > offsetInEdgeArrayS + minLineLen_ )
      {
        lineFitErr = LeastSquaresLineFit_( pEdgeXCors, pEdgeYCors, offsetInEdgeArrayS, lineEquation );
        if( lineFitErr <= lineFitErrThreshold_ )
          break;      //ok, an initial line segment detected
        offsetInEdgeArrayS += SkipEdgePoint;  //skip the first two pixel in the chain and try with the remaining pixels
      }
      if( lineFitErr > lineFitErrThreshold_ )
        break;  //no line is detected
      //An initial line segment is detected. Try to extend this line segment
      pLineSID[numOfLines] = offsetInLineArray;
      double coef1 = 0;     //for a line ax+by+c=0, coef1 = 1/sqrt(a^2+b^2);
      double pointToLineDis;      //for a line ax+by+c=0 and a point(xi, yi), pointToLineDis = coef1*|a*xi+b*yi+c|
      bool bExtended = true;
      bool bFirstTry = true;
      int numOfOutlier;     //to against noise, we accept a few outlier of a line.
      int tryTimes = 0;
      if( pdirImg[pEdgeYCors[offsetInEdgeArrayS] * imageWidth + pEdgeXCors[offsetInEdgeArrayS]] == Horizontal )
      {     //y=ax+b, i.e. ax-y+b=0
        while ( bExtended )
        {
          tryTimes++;
          if( bFirstTry )
          {
            bFirstTry = false;
            for ( int i = 0; i < minLineLen_; i++ )
            {     //First add the initial line segment to the line array
              pLineXCors[offsetInLineArray] = pEdgeXCors[offsetInEdgeArrayS];
              pLineYCors[offsetInLineArray++] = pEdgeYCors[offsetInEdgeArrayS++];
            }
          }
          else
          {     //after each try, line is extended, line equation should be re-estimated
            //adjust the line equation
            lineFitErr = LeastSquaresLineFit_( pLineXCors, pLineYCors, pLineSID[numOfLines], newOffsetS, offsetInLineArray, lineEquation );
          }
          coef1 = 1 / sqrt( lineEquation[0] * lineEquation[0] + 1 );
          numOfOutlier = 0;
          newOffsetS = offsetInLineArray;
          while ( offsetInEdgeArrayE > offsetInEdgeArrayS )
          {
            pointToLineDis = fabs( lineEquation[0] * pEdgeXCors[offsetInEdgeArrayS] - pEdgeYCors[offsetInEdgeArrayS] + lineEquation[1] ) * coef1;
            pLineXCors[offsetInLineArray] = pEdgeXCors[offsetInEdgeArrayS];
            pLineYCors[offsetInLineArray++] = pEdgeYCors[offsetInEdgeArrayS++];
            if( pointToLineDis > lineFitErrThreshold_ )
            {
              numOfOutlier++;
              if( numOfOutlier > 3 )
                break;
            }
            else
            {           //we count number of connective outliers.
              numOfOutlier = 0;
            }
          }
          //pop back the last few outliers from lines and return them to edge chain
          offsetInLineArray -= numOfOutlier;
          offsetInEdgeArrayS -= numOfOutlier;
          if( offsetInLineArray - newOffsetS > 0 && tryTimes < TryTime )
          {           //some new pixels are added to the line
          }
          else
          {
            bExtended = false;            //no new pixels are added.
          }
        }
        //the line equation coefficients,for line w1x+w2y+w3 =0, we normalize it to make w1^2+w2^2 = 1.
        std::vector<double> lineEqu( 3, 0 );
        lineEqu[0] = lineEquation[0] * coef1;
        lineEqu[1] = -1 * coef1;
        lineEqu[2] = lineEquation[1] * coef1;
        if( LineValidation_( pLineXCors, pLineYCors, pLineSID[numOfLines], offsetInLineArray, lineEqu, direction ) )
        {           //check the line
          //store the line equation coefficients
          lineEquations_.push_back( lineEqu );
          /*At last, compute the line endpoints and store them.
           *we project the first and last pixels in the pixelChain onto the best fit line
           *to get the line endpoints.
           *xp= (w2^2*x0-w1*w2*y0-w3*w1)/(w1^2+w2^2)
           *yp= (w1^2*y0-w1*w2*x0-w3*w2)/(w1^2+w2^2)  */
          std::vector<float> lineEndP( 4, 0 );          //line endpoints
          double a1 = lineEqu[1] * lineEqu[1];
          double a2 = lineEqu[0] * lineEqu[0];
          double a3 = lineEqu[0] * lineEqu[1];
          double a4 = lineEqu[2] * lineEqu[0];
          double a5 = lineEqu[2] * lineEqu[1];
          unsigned int Px = pLineXCors[pLineSID[numOfLines]];         //first pixel
          unsigned int Py = pLineYCors[pLineSID[numOfLines]];
          lineEndP[0] = (float) ( a1 * Px - a3 * Py - a4 );         //x
          lineEndP[1] = (float) ( a2 * Py - a3 * Px - a5 );         //y
          Px = pLineXCors[offsetInLineArray - 1];         //last pixel
          Py = pLineYCors[offsetInLineArray - 1];
          lineEndP[2] = (float) ( a1 * Px - a3 * Py - a4 );         //x
          lineEndP[3] = (float) ( a2 * Py - a3 * Px - a5 );         //y
          lineEndpoints_.push_back( lineEndP );
          lineDirection_.push_back( direction );
          numOfLines++;
        }
        else
        {
          offsetInLineArray = pLineSID[numOfLines];         // line was not accepted, the offset is set back
        }
      }
      else
      {         //x=ay+b, i.e. x-ay-b=0
        while ( bExtended )
        {
          tryTimes++;
          if( bFirstTry )
          {
            bFirstTry = false;
            for ( int i = 0; i < minLineLen_; i++ )
            {         //First add the initial line segment to the line array
              pLineXCors[offsetInLineArray] = pEdgeXCors[offsetInEdgeArrayS];
              pLineYCors[offsetInLineArray++] = pEdgeYCors[offsetInEdgeArrayS++];
            }
          }
          else
          {         //after each try, line is extended, line equation should be re-estimated
            //adjust the line equation
            lineFitErr = LeastSquaresLineFit_( pLineXCors, pLineYCors, pLineSID[numOfLines], newOffsetS, offsetInLineArray, lineEquation );
          }
          coef1 = 1 / sqrt( 1 + lineEquation[0] * lineEquation[0] );
          numOfOutlier = 0;
          newOffsetS = offsetInLineArray;
          while ( offsetInEdgeArrayE > offsetInEdgeArrayS )
          {
            pointToLineDis = fabs( pEdgeXCors[offsetInEdgeArrayS] - lineEquation[0] * pEdgeYCors[offsetInEdgeArrayS] - lineEquation[1] ) * coef1;
            pLineXCors[offsetInLineArray] = pEdgeXCors[offsetInEdgeArrayS];
            pLineYCors[offsetInLineArray++] = pEdgeYCors[offsetInEdgeArrayS++];
            if( pointToLineDis > lineFitErrThreshold_ )
            {
              numOfOutlier++;
              if( numOfOutlier > 3 )
                break;
            }
            else
            {           //we count number of connective outliers.
              numOfOutlier = 0;
            }
          }
          //pop back the last few outliers from lines and return them to edge chain
          offsetInLineArray -= numOfOutlier;
          offsetInEdgeArrayS -= numOfOutlier;
          if( offsetInLineArray - newOffsetS > 0 && tryTimes < TryTime )
          {           //some new pixels are added to the line
          }
          else
          {
            bExtended = false;            //no new pixels are added.
          }
        }
        //the line equation coefficients,for line w1x+w2y+w3 =0, we normalize it to make w1^2+w2^2 = 1.
        std::vector<double> lineEqu( 3, 0 );
        lineEqu[0] = 1 * coef1;
        lineEqu[1] = -lineEquation[0] * coef1;
        lineEqu[2] = -lineEquation[1] * coef1;

        if( LineValidation_( pLineXCors, pLineYCors, pLineSID[numOfLines], offsetInLineArray, lineEqu, direction ) )
        {           //check the line
          //store the line equation coefficients
          lineEquations_.push_back( lineEqu );
          /*At last, compute the line endpoints and store them.
           *we project the first and last pixels in the pixelChain onto the best fit line
           *to get the line endpoints.
           *xp= (w2^2*x0-w1*w2*y0-w3*w1)/(w1^2+w2^2)
           *yp= (w1^2*y0-w1*w2*x0-w3*w2)/(w1^2+w2^2)  */
          std::vector<float> lineEndP( 4, 0 );          //line endpoints
          double a1 = lineEqu[1] * lineEqu[1];
          double a2 = lineEqu[0] * lineEqu[0];
          double a3 = lineEqu[0] * lineEqu[1];
          double a4 = lineEqu[2] * lineEqu[0];
          double a5 = lineEqu[2] * lineEqu[1];
          unsigned int Px = pLineXCors[pLineSID[numOfLines]];         //first pixel
          unsigned int Py = pLineYCors[pLineSID[numOfLines]];
          lineEndP[0] = (float) ( a1 * Px - a3 * Py - a4 );         //x
          lineEndP[1] = (float) ( a2 * Py - a3 * Px - a5 );         //y
          Px = pLineXCors[offsetInLineArray - 1];         //last pixel
          Py = pLineYCors[offsetInLineArray - 1];
          lineEndP[2] = (float) ( a1 * Px - a3 * Py - a4 );         //x
          lineEndP[3] = (float) ( a2 * Py - a3 * Px - a5 );         //y
          lineEndpoints_.push_back( lineEndP );
          lineDirection_.push_back( direction );
          numOfLines++;
        }
        else
        {
          offsetInLineArray = pLineSID[numOfLines];         // line was not accepted, the offset is set back
        }
      }
      //Extract line segments from the remaining pixel; Current chain has been shortened already.
    }
  }         //end for(unsigned int edgeID=0; edgeID<edges.numOfEdges; edgeID++)

  pLineSID[numOfLines] = offsetInLineArray;
  lines.numOfLines = numOfLines;

  return 1;
}

double BinaryDescriptor::EDLineDetector::LeastSquaresLineFit_( unsigned int *xCors, unsigned int *yCors, unsigned int offsetS,
                                                               std::vector<double> &lineEquation )
{

  float * pMatT;
  float * pATA;
  double fitError = 0;
  double coef;
  unsigned char *pdirImg = dirImg_.data;
  unsigned int offset = offsetS;
  /*If the first pixel in this chain is horizontal,
   *then we try to find a horizontal line, y=ax+b;*/
  if( pdirImg[yCors[offsetS] * imageWidth + xCors[offsetS]] == Horizontal )
  {
    /*Build the system,and solve it using least square regression: mat * [a,b]^T = vec
     * [x0,1]         [y0]
     * [x1,1] [a]     [y1]
     *    .   [b]  =   .
     * [xn,1]         [yn]*/
    pMatT = fitMatT.ptr<float>();         //fitMatT = [x0, x1, ... xn; 1,1,...,1];
    for ( int i = 0; i < minLineLen_; i++ )
    {
      //*(pMatT+minLineLen_) = 1; //the value are not changed;
      * ( pMatT++ ) = (float) xCors[offsetS];
      fitVec[0][i] = (float) yCors[offsetS++];
    }
    ATA = fitMatT * fitMatT.t();
    ATV = fitMatT * fitVec.t();
    /* [a,b]^T = Inv(mat^T * mat) * mat^T * vec */
    pATA = ATA.ptr<float>();
    coef = 1.0 / ( double( pATA[0] ) * double( pATA[3] ) - double( pATA[1] ) * double( pATA[2] ) );
    //    lineEquation = svd.Invert(ATA) * matT * vec;
    lineEquation[0] = coef * ( double( pATA[3] ) * double( ATV[0][0] ) - double( pATA[1] ) * double( ATV[0][1] ) );
    lineEquation[1] = coef * ( double( pATA[0] ) * double( ATV[0][1] ) - double( pATA[2] ) * double( ATV[0][0] ) );
    /*compute line fit error */
    for ( int i = 0; i < minLineLen_; i++ )
    {
      //coef = double(yCors[offset]) - double(xCors[offset++]) * lineEquation[0] - lineEquation[1];
      coef = double( yCors[offset] ) - double( xCors[offset] ) * lineEquation[0] - lineEquation[1];
      offset++;
      fitError += coef * coef;
    }
    return sqrt( fitError );
  }
  /*If the first pixel in this chain is vertical,
   *then we try to find a vertical line, x=ay+b;*/
  if( pdirImg[yCors[offsetS] * imageWidth + xCors[offsetS]] == Vertical )
  {
    /*Build the system,and solve it using least square regression: mat * [a,b]^T = vec
     * [y0,1]         [x0]
     * [y1,1] [a]     [x1]
     *    .   [b]  =   .
     * [yn,1]         [xn]*/
    pMatT = fitMatT.ptr<float>();         //fitMatT = [y0, y1, ... yn; 1,1,...,1];
    for ( int i = 0; i < minLineLen_; i++ )
    {
      //*(pMatT+minLineLen_) = 1;//the value are not changed;
      * ( pMatT++ ) = (float) yCors[offsetS];
      fitVec[0][i] = (float) xCors[offsetS++];
    }
    ATA = fitMatT * ( fitMatT.t() );
    ATV = fitMatT * fitVec.t();
    /* [a,b]^T = Inv(mat^T * mat) * mat^T * vec */
    pATA = ATA.ptr<float>();
    coef = 1.0 / ( double( pATA[0] ) * double( pATA[3] ) - double( pATA[1] ) * double( pATA[2] ) );
    //    lineEquation = svd.Invert(ATA) * matT * vec;
    lineEquation[0] = coef * ( double( pATA[3] ) * double( ATV[0][0] ) - double( pATA[1] ) * double( ATV[0][1] ) );
    lineEquation[1] = coef * ( double( pATA[0] ) * double( ATV[0][1] ) - double( pATA[2] ) * double( ATV[0][0] ) );
    /*compute line fit error */
    for ( int i = 0; i < minLineLen_; i++ )
    {
      //coef = double(xCors[offset]) - double(yCors[offset++]) * lineEquation[0] - lineEquation[1];
      coef = double( xCors[offset] ) - double( yCors[offset] ) * lineEquation[0] - lineEquation[1];
      offset++;
      fitError += coef * coef;
    }
    return sqrt( fitError );
  }
  return 0;
}
double BinaryDescriptor::EDLineDetector::LeastSquaresLineFit_( unsigned int *xCors, unsigned int *yCors, unsigned int offsetS,
                                                               unsigned int newOffsetS, unsigned int offsetE, std::vector<double> &lineEquation )
{
  int length = offsetE - offsetS;
  int newLength = offsetE - newOffsetS;
  if( length <= 0 || newLength <= 0 )
  {
    std::cout << "EDLineDetector::LeastSquaresLineFit_ Error:"
        " the expected line index is wrong...offsetE = " << offsetE << ", offsetS=" << offsetS << ", newOffsetS=" << newOffsetS << std::endl;
    return -1;
  }
  if( lineEquation.size() != 2 )
  {
    std::cout << "SHOULD NOT BE != 2" << std::endl;
  }
  cv::Mat_<float> matT( 2, newLength );
  cv::Mat_<float> vec( newLength, 1 );
  float * pMatT;
  float * pATA;
  double coef;
  unsigned char *pdirImg = dirImg_.data;
  /*If the first pixel in this chain is horizontal,
   *then we try to find a horizontal line, y=ax+b;*/
  if( pdirImg[yCors[offsetS] * imageWidth + xCors[offsetS]] == Horizontal )
  {
    /*Build the new system,and solve it using least square regression: mat * [a,b]^T = vec
     * [x0',1]         [y0']
     * [x1',1] [a]     [y1']
     *    .    [b]  =   .
     * [xn',1]         [yn']*/
    pMatT = matT.ptr<float>();          //matT = [x0', x1', ... xn'; 1,1,...,1]
    for ( int i = 0; i < newLength; i++ )
    {
      * ( pMatT + newLength ) = 1;
      * ( pMatT++ ) = (float) xCors[newOffsetS];
      vec[0][i] = (float) yCors[newOffsetS++];
    }
    /* [a,b]^T = Inv(ATA + mat^T * mat) * (ATV + mat^T * vec) */
    tempMatLineFit = matT * matT.t();
    tempVecLineFit = matT * vec;
    ATA = ATA + tempMatLineFit;
    ATV = ATV + tempVecLineFit;
    pATA = ATA.ptr<float>();
    coef = 1.0 / ( double( pATA[0] ) * double( pATA[3] ) - double( pATA[1] ) * double( pATA[2] ) );
    lineEquation[0] = coef * ( double( pATA[3] ) * double( ATV[0][0] ) - double( pATA[1] ) * double( ATV[0][1] ) );
    lineEquation[1] = coef * ( double( pATA[0] ) * double( ATV[0][1] ) - double( pATA[2] ) * double( ATV[0][0] ) );

    return 0;
  }
  /*If the first pixel in this chain is vertical,
   *then we try to find a vertical line, x=ay+b;*/
  if( pdirImg[yCors[offsetS] * imageWidth + xCors[offsetS]] == Vertical )
  {
    /*Build the system,and solve it using least square regression: mat * [a,b]^T = vec
     * [y0',1]         [x0']
     * [y1',1] [a]     [x1']
     *    .    [b]  =   .
     * [yn',1]         [xn']*/
    pMatT = matT.ptr<float>();          //matT = [y0', y1', ... yn'; 1,1,...,1]
    for ( int i = 0; i < newLength; i++ )
    {
      * ( pMatT + newLength ) = 1;
      * ( pMatT++ ) = (float) yCors[newOffsetS];
      vec[0][i] = (float) xCors[newOffsetS++];
    }
    /* [a,b]^T = Inv(ATA + mat^T * mat) * (ATV + mat^T * vec) */
//    matT.MultiplyWithTransposeOf(matT, tempMatLineFit);
    tempMatLineFit = matT * matT.t();
    tempVecLineFit = matT * vec;
    ATA = ATA + tempMatLineFit;
    ATV = ATV + tempVecLineFit;
//    pATA = ATA.GetData();
    pATA = ATA.ptr<float>();
    coef = 1.0 / ( double( pATA[0] ) * double( pATA[3] ) - double( pATA[1] ) * double( pATA[2] ) );
    lineEquation[0] = coef * ( double( pATA[3] ) * double( ATV[0][0] ) - double( pATA[1] ) * double( ATV[0][1] ) );
    lineEquation[1] = coef * ( double( pATA[0] ) * double( ATV[0][1] ) - double( pATA[2] ) * double( ATV[0][0] ) );

  }
  return 0;
}

bool BinaryDescriptor::EDLineDetector::LineValidation_( unsigned int *xCors, unsigned int *yCors, unsigned int offsetS, unsigned int offsetE,
                                                        std::vector<double> &lineEquation, float &direction )
{
  if( bValidate_ )
  {
    int n = offsetE - offsetS;
    /*first compute the direction of line, make sure that the dark side always be the
     *left side of a line.*/
    int meanGradientX = 0, meanGradientY = 0;
    short *pdxImg = dxImg_.ptr<short>();
    short *pdyImg = dyImg_.ptr<short>();
    double dx, dy;
    std::vector<double> pointDirection;
    int index;
    for ( int i = 0; i < n; i++ )
    {
      index = yCors[offsetS] * imageWidth + xCors[offsetS];
      offsetS++;
      meanGradientX += pdxImg[index];
      meanGradientY += pdyImg[index];
      dx = (double) pdxImg[index];
      dy = (double) pdyImg[index];
      pointDirection.push_back( atan2( -dx, dy ) );
    }
    dx = fabs( lineEquation[1] );
    dy = fabs( lineEquation[0] );
    if( meanGradientX == 0 && meanGradientY == 0 )
    {         //not possible, if happens, it must be a wrong line,
      return false;
    }
    if( meanGradientX > 0 && meanGradientY >= 0 )
    {         //first quadrant, and positive direction of X axis.
      direction = (float) atan2( -dy, dx );         //line direction is in fourth quadrant
    }
    if( meanGradientX <= 0 && meanGradientY > 0 )
    {         //second quadrant, and positive direction of Y axis.
      direction = (float) atan2( dy, dx );          //line direction is in first quadrant
    }
    if( meanGradientX < 0 && meanGradientY <= 0 )
    {         //third quadrant, and negative direction of X axis.
      direction = (float) atan2( dy, -dx );         //line direction is in second quadrant
    }
    if( meanGradientX >= 0 && meanGradientY < 0 )
    {         //fourth quadrant, and negative direction of Y axis.
      direction = (float) atan2( -dy, -dx );          //line direction is in third quadrant
    }
    /*then check whether the line is on the border of the image. We don't keep the border line.*/
    if( fabs( direction ) < 0.15 || M_PI - fabs( direction ) < 0.15 )
    {         //Horizontal line
      if( fabs( lineEquation[2] ) < 10 || fabs( imageHeight - fabs( lineEquation[2] ) ) < 10 )
      {         //upper border or lower border
        return false;
      }
    }
    if( fabs( fabs( direction ) - M_PI * 0.5 ) < 0.15 )
    {         //Vertical line
      if( fabs( lineEquation[2] ) < 10 || fabs( imageWidth - fabs( lineEquation[2] ) ) < 10 )
      {         //left border or right border
        return false;
      }
    }
    //count the aligned points on the line which have the same direction as the line.
    double disDirection;
    int k = 0;
    for ( int i = 0; i < n; i++ )
    {
      disDirection = fabs( direction - pointDirection[i] );
      if( fabs( 2 * M_PI - disDirection ) < 0.392699 || disDirection < 0.392699 )
      {         //same direction, pi/8 = 0.392699081698724
        k++;
      }
    }
    //now compute NFA(Number of False Alarms)
    double ret = nfa( n, k, 0.125, logNT_ );

    return ( ret > 0 );  //0 corresponds to 1 mean false alarm
  }
  else
  {
    return true;
  }
}

int BinaryDescriptor::EDLineDetector::EDline( cv::Mat &image )
{
  if( ( EDline( image, lines_/*, smoothed*/) ) != 1 )
  {
    return -1;
  }
  lineSalience_.clear();
  lineSalience_.resize( lines_.numOfLines );
  unsigned char *pgImg = gImgWO_.ptr();
  unsigned int indexInLineArray;
  unsigned int *pXCor = &lines_.xCors.front();
  unsigned int *pYCor = &lines_.yCors.front();
  unsigned int *pSID = &lines_.sId.front();
  for ( unsigned int i = 0; i < lineSalience_.size(); i++ )
  {
    int salience = 0;
    for ( indexInLineArray = pSID[i]; indexInLineArray < pSID[i + 1]; indexInLineArray++ )
    {
      salience += pgImg[pYCor[indexInLineArray] * imageWidth + pXCor[indexInLineArray]];
    }
    lineSalience_[i] = (float) salience;
  }
  return 1;
}

}
}
