generic-library/opencv
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Fixed several merge issues

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This commit is contained in:
Maksim Shabunin 2016-07-13 11:45:32 +03:00
parent 74b83cfce5
commit 2a350b11dd
2 changed files with 17 additions and 23 deletions
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9
modules/calib3d/include/opencv2/calib3d/calib3d.hpp
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@ -46,12 +46,3 @@
#endif
#include "opencv2/calib3d.hpp"
// Performs a fast check if a chessboard is in the input image. This is a workaround to
// a problem of cvFindChessboardCorners being slow on images with no chessboard.
// This method works using a binary image as input
// - src: input binary image
// - size: chessboard size
// Returns 1 if a chessboard can be in this image and findChessboardCorners should be called,
// 0 if there is no chessboard, -1 in case of error
CVAPI(int) cvCheckChessboardBinary(IplImage* src, CvSize size);

31
modules/calib3d/src/calibinit.cpp
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@ -202,6 +202,8 @@ static void icvRemoveQuadFromGroup(CvCBQuad **quads, int count, CvCBQuad *q0);
static int icvCheckBoardMonotony( CvPoint2D32f* corners, CvSize pattern_size );
int cvCheckChessboardBinary(IplImage* src, CvSize size);
/***************************************************************************************************/
//COMPUTE INTENSITY HISTOGRAM OF INPUT IMAGE
static int icvGetIntensityHistogram( unsigned char* pucImage, int iSizeCols, int iSizeRows, std::vector<int>& piHist );
@ -515,7 +517,7 @@ int cvFindChessboardCorners( const void* arr, CvSize pattern_size,
//perform new method for checking chessboard using a binary image.
//image is binarised using a threshold dependent on the image histogram
icvBinarizationHistogramBased( (unsigned char*) cImgSeg->imageData, cImgSeg->width, cImgSeg->height );
check_chessboard_result = cvCheckChessboardBinary(cImgSeg, pattern_size);
int check_chessboard_result = cvCheckChessboardBinary(cImgSeg, pattern_size);
if(check_chessboard_result <= 0) //fall back to the old method
{
IplImage _img;
@ -528,16 +530,6 @@ int cvFindChessboardCorners( const void* arr, CvSize pattern_size,
}
}
// empiric threshold level
// thresholding performed here and not inside the cycle to save processing time
int thresh_level;
if ( !(flags & CV_CALIB_CB_ADAPTIVE_THRESH) )
{
double mean = cvAvg( img ).val[0];
thresh_level = cvRound( mean - 10 );
thresh_level = MAX( thresh_level, 10 );
cvThreshold( img, thresh_img, thresh_level, 255, CV_THRESH_BINARY );
}
// Try our standard "1" dilation, but if the pattern is not found, iterate the whole procedure with higher dilations.
// This is necessary because some squares simply do not separate properly with a single dilation. However,
// we want to use the minimum number of dilations possible since dilations cause the squares to become smaller,
@ -550,6 +542,8 @@ int cvFindChessboardCorners( const void* arr, CvSize pattern_size,
cvFree(&quads);
cvFree(&corners);
int max_quad_buf_size = 0;
//USE BINARY IMAGE COMPUTED USING icvBinarizationHistogramBased METHOD
cvDilate( thresh_img_new, thresh_img_new, 0, 1 );
@ -586,8 +580,7 @@ int cvFindChessboardCorners( const void* arr, CvSize pattern_size,
// order the quad corners globally
// maybe delete or add some
PRINTF("Starting ordering of inner quads\n");
count = icvOrderFoundConnectedQuads(count, quad_group, &quad_count, &quads, &corners,
pattern_size, storage );
count = icvOrderFoundConnectedQuads(count, quad_group, &quad_count, &quads, &corners, pattern_size, max_quad_buf_size, storage );
PRINTF("Orig count: %d After ordering: %d\n", icount, count);
if (count == 0)
@ -637,6 +630,16 @@ int cvFindChessboardCorners( const void* arr, CvSize pattern_size,
// revert to old, slower, method if detection failed
if (!found)
{
// empiric threshold level
// thresholding performed here and not inside the cycle to save processing time
int thresh_level;
if ( !(flags & CV_CALIB_CB_ADAPTIVE_THRESH) )
{
double mean = cvAvg( img ).val[0];
thresh_level = cvRound( mean - 10 );
thresh_level = MAX( thresh_level, 10 );
cvThreshold( img, thresh_img, thresh_level, 255, CV_THRESH_BINARY );
}
for( k = 0; k < 6; k++ )
{
int max_quad_buf_size = 0;
@ -669,7 +672,7 @@ int cvFindChessboardCorners( const void* arr, CvSize pattern_size,
}
#ifdef DEBUG_CHESSBOARD
cvCvtColor(thresh_img,dbg_img,CV_GRAY2BGR);
cvCvtColor(thresh_img,dbg_img,CV_GRAY2BGR);
#endif
// So we can find rectangles that go to the edge, we draw a white line around the image edge.