//正方形检测源码 //载入数张包含各种形状的图片,检测出其中的正方形 #include "cv.h" #include "highgui.h" #include <stdio.h> #include <math.h> #include <string.h> #include <iostream> int thresh = 50; IplImage* img =NULL; IplImage* img0 = NULL; CvMemStorage* storage =NULL; const char * wndname = "正方形检测 demo"; //angle函数用来返回(两个向量之间找到角度的余弦值) 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); } // 返回图像中找到的所有轮廓序列,并且序列存储在内存存储器中 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 ); 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; // 创建一个空序列用于存储轮廓角点 CvSeq* squares = cvCreateSeq( 0, sizeof(CvSeq), sizeof(CvPoint), storage ); cvSetImageROI( timg, cvRect( 0, 0, sz.width, sz.height )); // 过滤噪音 cvPyrDown( timg, pyr, 7 ); cvPyrUp( pyr, timg, 7 ); tgray = cvCreateImage( sz, 8, 1 ); // 红绿蓝3色分别尝试提取 for( c = 0; c < 3; c++ ) { // 提取 the c-th color plane cvSetImageCOI( timg, c+1 ); cvCopy( timg, tgray, 0 ); // 尝试各种阈值提取得到的(N=11) for( l = 0; l < N; l++ ) { // apply Canny. Take the upper threshold from slider // Canny helps to catch squares with gradient shading if( l == 0 ) { cvCanny( tgray, gray, 0, thresh, 5 ); //使用任意结构元素膨胀图像 cvDilate( gray, gray, 0, 1 ); } else { // apply threshold if l!=0: cvThreshold( tgray, gray, (l+1)*255/N, 255, CV_THRESH_BINARY ); } // 找到所有轮廓并且存储在序列中 cvFindContours( gray, storage, &contours, sizeof(CvContour), CV_RETR_LIST, CV_CHAIN_APPROX_SIMPLE, cvPoint(0,0) ); // 遍历找到的每个轮廓contours while( contours ) { //用指定精度逼近多边形曲线 result = cvApproxPoly( contours, sizeof(CvContour), storage, CV_POLY_APPROX_DP, cvContourPerimeter(contours)*0.02, 0 ); if( result->total == 4 && fabs(cvContourArea(result,CV_WHOLE_SEQ)) > 500 && fabs(cvContourArea(result,CV_WHOLE_SEQ)) < 100000 && 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 余弦值 足够小,可以认定角度为90度直角 //cos0.1=83度,能较好的趋近直角 if( s < 0.1 ) for( i = 0; i < 4; i++ ) cvSeqPush( squares, (CvPoint*)cvGetSeqElem( result, i )); } // 继续查找下一个轮廓 contours = contours->h_next; } } } cvReleaseImage( &gray ); cvReleaseImage( &pyr ); cvReleaseImage( &tgray ); cvReleaseImage( &timg ); return squares; } //drawSquares函数用来画出在图像中找到的所有正方形轮廓 void drawSquares( IplImage* img, CvSeq* squares ) { CvSeqReader reader; IplImage* cpy = cvCloneImage( img ); int i; 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), 2, CV_AA, 0 ); } cvShowImage( wndname, cpy ); cvReleaseImage( &cpy ); } char* names[] = { "pic1.png", "pic2.png", "pic3.png", "pic4.png", "pic5.png", "pic6.png","pic7.png","pic8.png", "pic9.png","pic10.png","pic11.png","pic12.png", 0 }; int main(int argc, char** argv) { int i, c; storage = cvCreateMemStorage(0); for( i = 0; names[i] != 0; i++ ) { img0 = cvLoadImage( names[i], 1 ); if( !img0 ) { cout<<"不能载入"<<names[i]<<"继续下一张图片"<<endl; continue; } img = cvCloneImage( img0 ); cvNamedWindow( wndname, 1 ); // find and draw the squares drawSquares( img, findSquares4( img, storage ) ); c = cvWaitKey(0); cvReleaseImage( &img ); cvReleaseImage( &img0 ); cvClearMemStorage( storage ); if( (char)c == 27 ) break; } cvDestroyWindow( wndname ); return 0; }