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Improvement of color filtering algorithm for the contour detection :

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hue / saturation histogram used instead of a simple hue histogram
This commit is contained in:
rnc 2012-03-26 10:07:53 +00:00
parent d2e5c01511
commit e98f44ce25
1 changed files with 25 additions and 13 deletions
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38
src/ShapeRecognition/ShapeRec_FeatureDetector.cxx
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@ -240,20 +240,25 @@ Mat ShapeRec_FeatureDetector::_colorFiltering()
cvResetImageROI(find_image);
IplImage* test_hsv = cvCreateImage(cvGetSize(test_image),8,3);
IplImage* test_hue = cvCreateImage(cvGetSize(test_image),8,1);
IplImage* h_plane = cvCreateImage( cvGetSize(test_image), 8, 1 );
IplImage* s_plane = cvCreateImage( cvGetSize(test_image), 8, 1 );
CvHistogram* hist;
cvCvtColor(test_image, test_hsv, CV_BGR2HSV);
cvCvtPixToPlane(test_hsv, test_hue, 0, 0, 0);
cvCvtPixToPlane(test_hsv, h_plane, s_plane, 0, 0);
IplImage* planes[] = { h_plane, s_plane };
//create hist
int size_hist = 10;
float hranges[] = {0, 180};
float* ranges = hranges;
hist = cvCreateHist(1, &size_hist, CV_HIST_ARRAY, &ranges, 1);
int hbins = 30, sbins = 32; // TODO think to the best values here
int hist_size[] = { hbins, sbins };
float hranges[] = { 0, 180 };
float sranges[] = { 0, 255 };
float* ranges[] = { hranges, sranges };
hist = cvCreateHist(2, hist_size, CV_HIST_ARRAY, ranges, 1);
//calculate hue` histogram
cvCalcHist(&test_hue, hist, 0 ,0);
//calculate hue /saturation histogram
cvCalcHist(planes, hist, 0 ,0);
// // TEST print of the histogram for debugging
// IplImage* hist_image = cvCreateImage(cvSize(320,300),8,3);
@ -279,21 +284,28 @@ Mat ShapeRec_FeatureDetector::_colorFiltering()
// cvNamedWindow("hist", 1); cvShowImage("hist",hist_image);
//calculate back projection of hue plane of input image
//calculate back projection of hue and saturation planes of input image
IplImage* backproject = cvCreateImage(cvGetSize(find_image), 8, 1);
IplImage* binary_backproject = cvCreateImage(cvGetSize(find_image), 8, 1);
IplImage* find_hsv = cvCreateImage(cvGetSize(find_image),8,3);
IplImage* find_hue = cvCreateImage(cvGetSize(find_image),8,1);
IplImage* find_hplane = cvCreateImage(cvGetSize(find_image),8,1);
IplImage* find_splane = cvCreateImage(cvGetSize(find_image),8,1);
cvCvtColor(find_image, find_hsv, CV_BGR2HSV);
cvCvtPixToPlane(find_hsv, find_hue, 0, 0, 0);
cvCalcBackProject(&find_hue, backproject, hist);
cvCvtPixToPlane(find_hsv, find_hplane, find_splane, 0, 0);
IplImage* find_planes[] = { find_hplane, find_splane };
cvCalcBackProject(find_planes, backproject, hist);
// Threshold in order to obtain binary image
cvThreshold(backproject, binary_backproject, 1, 255, CV_THRESH_BINARY); // NOTE it would be good to think about the best threshold to use (it's 1 for now)
cvReleaseImage(&test_image);
cvReleaseImage(&test_hsv);
cvReleaseImage(&test_hue);
cvReleaseImage(&h_plane);
cvReleaseImage(&s_plane);
cvReleaseImage(&find_image);
cvReleaseImage(&find_hsv);
cvReleaseImage(&find_hplane);
cvReleaseImage(&find_splane);
cvReleaseImage(&backproject);
return Mat(binary_backproject);