-// Copyright (C) 2007-2011 CEA/DEN, EDF R&D, OPEN CASCADE
+// Copyright (C) 2007-2012 CEA/DEN, EDF R&D, OPEN CASCADE
//
// Copyright (C) 2003-2007 OPEN CASCADE, EADS/CCR, LIP6, CEA/DEN,
// CEDRAT, EDF R&D, LEG, PRINCIPIA R&D, BUREAU VERITAS
// Foundation, Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA
//
// See http://www.salome-platform.org/ or email : webmaster.salome@opencascade.com
+//
// File : ShapeRec_FeatureDetector.cxx
// Author : Renaud NEDELEC, Open CASCADE S.A.S.
Constructor
\param theFilename - image to process
*/
-ShapeRec_FeatureDetector::ShapeRec_FeatureDetector(const QString& theFilename):
+ShapeRec_FeatureDetector::ShapeRec_FeatureDetector():
corners()
{
cornerCount = 2000;
rect=cvRect(0,0,0,0);
- imagePath = theFilename.toStdString();
+ imagePath = ""; //theFilename;
// Store the dimensions of the picture
- IplImage* bg_img = cvLoadImage (imagePath.c_str(), CV_LOAD_IMAGE_GRAYSCALE);
- imgHeight = bg_img->height;
- imgWidth = bg_img->width;
+ imgHeight = 0;
+ imgWidth = 0;
+}
+
+/*!
+ Sets the path of the image file to be processed
+ \param thePath - Location of the image file
+*/
+void ShapeRec_FeatureDetector::SetPath( const std::string& thePath )
+{
+ imagePath = thePath;
+ if (imagePath != "")
+ {
+ IplImage* src = cvLoadImage(imagePath.c_str(),CV_LOAD_IMAGE_COLOR);
+ imgHeight = src->height;
+ imgWidth = src->width;
+ }
}
/*!
}
}
+/*!
+ Crops the image located at imagePath to the region of interest given by the user via SetROI
+ and stores the result in /tmp
+ \param theRect - Region Of Interest of the image located at imagePath
+*/
+std::string ShapeRec_FeatureDetector::CroppImage()
+{
+ IplImage* src = cvLoadImage(imagePath.c_str(),CV_LOAD_IMAGE_COLOR);
+
+ cvSetImageROI(src, rect);
+ IplImage* cropped_image = cvCreateImage(cvGetSize(src),
+ src->depth,
+ src->nChannels);
+ cvCopy(src, cropped_image, NULL);
+ cvResetImageROI(src);
+
+ cvSaveImage ("/tmp/cropped_image.bmp", cropped_image);
+
+ return "/tmp/cropped_image.bmp";
+}
+
+
/*!
Performs contours detection and store them in contours
- \param src - src image to find contours of
+ \param binaryImg - src image to find contours of
*/
-void ShapeRec_FeatureDetector::_detectAndRetrieveContours( Mat src )
+void ShapeRec_FeatureDetector::_detectAndRetrieveContours( Mat binaryImg )
{
- src = src > 1;
+ binaryImg = binaryImg > 1;
int method = CV_CHAIN_APPROX_NONE;
- findContours( src, contours, hierarchy,CV_RETR_CCOMP, method);
+ findContours( binaryImg, contours, hierarchy,CV_RETR_CCOMP, method);
// Other possible approximations CV_CHAIN_APPROX_TC89_KCOS, CV_CHAIN_APPROX_TC89_L1, CV_CHAIN_APPROX_SIMPLE cf. OpenCV documentation
// for precise information
}
// Crop the image to build an histogram from the selected part
cvSetImageROI(find_image, rect);
IplImage* test_image = cvCreateImage(cvGetSize(find_image),
- find_image->depth,
- find_image->nChannels);
+ find_image->depth,
+ find_image->nChannels);
cvCopy(find_image, test_image, NULL);
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);
// 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);
