#include "imageprocessing.h" #define H_PIXEL(i,j,image) ((uchar*)((image)->imageData))[((i) * (image)->widthStep) + ((j) * (image)->nChannels)] #define S_PIXEL(i,j,image) ((uchar*)((image)->imageData))[(((i) * (image)->widthStep) + ((j) * (image)->nChannels)) + 1] #define V_PIXEL(i,j,image) ((uchar*)((image)->imageData))[(((i) * (image)->widthStep) + ((j) * (image)->nChannels)) + 2] #define SET_PIXEL_V1(i,j,image,x) ((uchar*)((image)->imageData))[((i) * (image)->widthStep) + ((j) * (image)->nChannels)] = (x) #define MAXHUE 360 #include // taken from unixrobot int findColor(IplImage* image, IplImage* resultImage,Configuration *configuration, Colorpixels *cp) { int i, j; // hue is between 0 and 360 int hlower = configuration->getIntParam( "hue-lower-limit"); int hupper = configuration->getIntParam( "hue-upper-limit"); int slower = configuration->getIntParam( "saturation-lower-limit"); int supper = configuration->getIntParam( "saturation-upper-limit"); int vlower = configuration->getIntParam( "value-lower-limit"); int vupper = configuration->getIntParam( "value-upper-limit"); IplImage *imageHSV = cvCloneImage(image); cvCvtColor(imageHSV, imageHSV, CV_BGR2HSV); // Converting the color space uchar *data = (uchar *) imageHSV->imageData; // clearing the result image cvZero(resultImage); assert(imageHSV->height == resultImage->height); assert(imageHSV->width == resultImage->width); cp->left = 0; cp->right = 0; //cout << hlower << " " << hupper << " " << slower << " " << supper << " " << vlower << " " << vupper << endl; for (i = 0; i < image->height; i++) { for (j = 0; j < image->width; j++) { if ( (2 * H_PIXEL(i, j, imageHSV) - hlower + MAXHUE) % MAXHUE <= (hupper - hlower + MAXHUE) % MAXHUE && S_PIXEL(i, j, imageHSV) >= slower && S_PIXEL(i, j, imageHSV) <= supper && V_PIXEL(i, j, imageHSV) >= vlower && V_PIXEL(i, j, imageHSV) <= vupper ) { SET_PIXEL_V1(i, j, resultImage, 255); if( j < image->width/2 ) { ++cp->left; } else { ++cp->right; } } } } cvReleaseImage(&imageHSV); for (i = 0; i < configuration->getIntParam( "dilate_erode_number"); ++i) { cvDilate(resultImage, resultImage); cvErode(resultImage, resultImage); } return 1; } int thresh = 50; // helper function: // finds a cosine of angle between vectors // from pt0->pt1 and from pt0->pt2 double angle( CvPoint* pt1, CvPoint* pt2, CvPoint* pt0 ) { double dx1 = pt1->x - pt0->x; double dy1 = pt1->y - pt0->y; double dx2 = pt2->x - pt0->x; double dy2 = pt2->y - pt0->y; return (dx1*dx2 + dy1*dy2)/sqrt((dx1*dx1 + dy1*dy1)*(dx2*dx2 + dy2*dy2) + 1e-10); } // returns sequence of squares detected on the image. // the sequence is stored in the specified memory storage CvSeq* findSquares4( IplImage* img, CvMemStorage* storage ) { CvSeq* contours; int i, c, l, N = 11; CvSize sz = cvSize( img->width & -2, img->height & -2 ); IplImage* timg = cvCloneImage( img ); // make a copy of input image IplImage* gray = cvCreateImage( sz, 8, 1 ); IplImage* pyr = cvCreateImage( cvSize(sz.width/2, sz.height/2), 8, 3 ); IplImage* tgray; CvSeq* result; double s, t; // create empty sequence that will contain points - // 4 points per square (the square's vertices) CvSeq* squares = cvCreateSeq( 0, sizeof(CvSeq), sizeof(CvPoint), storage ); // select the maximum ROI in the image // with the width and height divisible by 2 cvSetImageROI( timg, cvRect( 0, 0, sz.width, sz.height )); // down-scale and upscale the image to filter out the noise //cvPyrDown( timg, pyr, 7 ); //cvPyrUp( pyr, timg, 7 ); tgray = cvCreateImage( sz, 8, 1 ); // find squares in every color plane of the image for( c = 0; c < 3; c++ ) { // extract the c-th color plane cvSetImageCOI( timg, c+1 ); cvCopy( timg, tgray, 0 ); // try several threshold levels for( l = 0; l < N; l++ ) { // hack: use Canny instead of zero threshold level. // Canny helps to catch squares with gradient shading if( l == 0 ) { // apply Canny. Take the upper threshold from slider // and set the lower to 0 (which forces edges merging) cvCanny( tgray, gray, 0, thresh, 5 ); // dilate canny output to remove potential // holes between edge segments cvDilate( gray, gray, 0, 1 ); } else { // apply threshold if l!=0: // tgray(x,y) = gray(x,y) < (l+1)*255/N ? 255 : 0 cvThreshold( tgray, gray, (l+1)*255/N, 255, CV_THRESH_BINARY ); } // find contours and store them all as a list cvFindContours( gray, storage, &contours, sizeof(CvContour), CV_RETR_LIST, CV_CHAIN_APPROX_SIMPLE, cvPoint(0,0) ); // test each contour while( contours ) { // approximate contour with accuracy proportional // to the contour perimeter result = cvApproxPoly( contours, sizeof(CvContour), storage, CV_POLY_APPROX_DP, cvContourPerimeter(contours)*0.02, 0 ); // square contours should have 4 vertices after approximation // relatively large area (to filter out noisy contours) // and be convex. // Note: absolute value of an area is used because // area may be positive or negative - in accordance with the // contour orientation if( result->total == 4 && fabs(cvContourArea(result,CV_WHOLE_SEQ)) > 1000 && cvCheckContourConvexity(result) ) { s = 0; for( i = 0; i < 5; i++ ) { // find minimum angle between joint // edges (maximum of cosine) if( i >= 2 ) { t = fabs(angle( (CvPoint*)cvGetSeqElem( result, i ), (CvPoint*)cvGetSeqElem( result, i-2 ), (CvPoint*)cvGetSeqElem( result, i-1 ))); s = s > t ? s : t; } } // if cosines of all angles are small // (all angles are ~90 degree) then write quandrange // vertices to resultant sequence if( s < 0.3 ) for( i = 0; i < 4; i++ ) cvSeqPush( squares, (CvPoint*)cvGetSeqElem( result, i )); } // take the next contour contours = contours->h_next; } } } // release all the temporary images cvReleaseImage( &gray ); cvReleaseImage( &pyr ); cvReleaseImage( &tgray ); cvReleaseImage( &timg ); return squares; } const char* wndname = "Square Detection Demo"; // the function draws all the squares in the image void drawSquares( IplImage* img, CvSeq* squares ) { CvSeqReader reader; IplImage* cpy = cvCloneImage( img ); int i; // initialize reader of the sequence cvStartReadSeq( squares, &reader, 0 ); // read 4 sequence elements at a time (all vertices of a square) for( i = 0; i < squares->total; i += 4 ) { CvPoint pt[4], *rect = pt; int count = 4; // read 4 vertices CV_READ_SEQ_ELEM( pt[0], reader ); CV_READ_SEQ_ELEM( pt[1], reader ); CV_READ_SEQ_ELEM( pt[2], reader ); CV_READ_SEQ_ELEM( pt[3], reader ); // draw the square as a closed polyline cvPolyLine( cpy, &rect, &count, 1, 1, CV_RGB(0,255,0), 3, CV_AA, 0 ); } // show the resultant image cvShowImage( wndname, cpy ); cvReleaseImage( &cpy ); }