opencv识别三角形代码（转）

#include "cv.h"#include "highgui.h"#include #include #include #include

int thresh = 50;IplImage* img =NULL;IplImage* img0 = NULL;CvMemStorage* storage =NULL;const char * wndname = "三角形识别 Demo";

// 两个向量之间找到角度的余弦值// from pt0->pt1 and from pt0->pt2double 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);}

// 返回图像中找到的轮廓序列// 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和角点 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 );

 // find squares in every color plane of the image for( c = 0; c < 3; c++ ) {  // 提取 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 );   }

   // 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) );

   // 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 );    // 三角形轮廓应当有3个顶点,3条边    // relatively large area (过滤干扰的轮廓)    // cvCheckContourConvexity保证是凸面的    // cvContourArea计算三角形区域面积，去掉一些不相干的区域    if( result->total == 3 &&     fabs(cvContourArea(result,CV_WHOLE_SEQ)) > 1000 &&     fabs(cvContourArea(result,CV_WHOLE_SEQ)) < 100000 &&     cvCheckContourConvexity(result) )    {     

      for( i = 0; i < 3; i++ )       cvSeqPush( squares,       (CvPoint*)cvGetSeqElem( result, i ));    }

    // 继续查找下一个轮廓    contours = contours->h_next;   }  } }

 // release all the temporary images cvReleaseImage( &gray ); cvReleaseImage( &pyr ); cvReleaseImage( &tgray ); cvReleaseImage( &timg );

 return squares;}

// the function draws all the squares in the imagevoid 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 += 3 ) {  CvPoint pt[3], *rect = pt;  int count = 3;

  // read 3 vertices  CV_READ_SEQ_ELEM( pt[0], reader );  CV_READ_SEQ_ELEM( pt[1], reader );  CV_READ_SEQ_ELEM( pt[2], reader );

  // cvPolyLine函数画出三角形轮廓  cvPolyLine( cpy, &rect, &count, 1, 1, CV_RGB(0,255,0), 3, CV_AA, 0 ); }

 // show the resultant image 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; // create memory storage that will contain all the dynamic data storage = cvCreateMemStorage(0);

 for( i = 0; names[i] != 0; i++ ) {  img0 = cvLoadImage( names[i], 1 );  if( !img0 )  {   cout