opencv图像处理6--网球检测

布满荆棘的人生 2022-06-18 04:45 285阅读 0赞

void CBallsampleDlg::OnOK()   
\{  
// TODO: Add extra validation here  
  
  
  
  
  
//CDialog::OnOK();  
IplImage\*frame = NULL;  //定义帧,每帧就是一张图    
IplImage\* B\_part = NULL;  
IplImage\* G\_part = NULL;  
IplImage\* R\_part = NULL;//三个通道下的灰度图  
IplImage\* biImage = NULL;//调试用，G通道二值化后的灰度图  
IplImage\* biImage\_B = NULL;//B通道下进行阈值分割后的图片。  
IplImage\* dst = NULL;   
  
  
  
CvMemStorage\* storage = cvCreateMemStorage(0);  
CvMemStorage\* circleStorage = cvCreateMemStorage(0);  
CvSeq\* contour = 0;  
   
//轮廓矩形  
CvRect contourRect = cvRect(0,0,0,0);  
  
  
CvCapture \* pCapture = cvCreateFileCapture("x1.avi");  
// CvCapture\* pCapture = cvCreateCameraCapture(-1); //创建摄像头抓取    
  
  
cvNamedWindow("Camera",CV\_WINDOW\_AUTOSIZE);  //设置窗口    
    cvNamedWindow("contours",1);  
cvNamedWindow("B\_channel",1);  
cvNamedWindow("G\_channel",1);  
cvNamedWindow("R\_channel",1);  
    cvNamedWindow("circle",1);  
    cvNamedWindow("biImage",1);  
cvNamedWindow("biImage\_B",1);  
  
  
  
  
  
int count = 1;  
while (frame = cvQueryFrame(pCapture))        
\{      
if(count ==1)  
\{  
//读取第一帧图片后，初始化各个图片  
B\_part = cvCreateImage(cvGetSize(frame),frame->depth,1);  
G\_part = cvCreateImage(cvGetSize(frame),frame->depth,1);  
R\_part = cvCreateImage(cvGetSize(frame),frame->depth,1);  
    biImage = cvCreateImage(cvGetSize(frame),frame->depth,1);  
biImage\_B = cvCreateImage(cvGetSize(frame),frame->depth,1);  
dst = cvCreateImage( cvGetSize(frame), 8, 3 );  
\}  
else\{  
//开始进行图像处理  
cvSplit(frame , B\_part,G\_part, R\_part,0);//抽取单个通道  
// cvFlip(G\_part,G\_part,0);//沿X轴翻转一次  
CvSeq\* circles = cvHoughCircles( G\_part, circleStorage, CV\_HOUGH\_GRADIENT, 2, G\_part->height/4, 200, 100 );  
//circles存储找到的圆形物体，本打算采用形状的方式找到网球，但是由于干扰物种存在圆形物体，因此干扰很严重  
//并且，由于光线的不均匀，网球的一部分灰度值比较低，因此采用形状判别，效果不佳~  
//最终才用的是在两个通道下分别去掉一部分干扰物，两个二值图再进行与操作。  
  
  
//绘制找到的圆，测试表明总是会找到干扰圆，而不是要找的网球。  
for(int i = 0; i < circles->total; i++ )  
\{  
float\* p = (float\*)cvGetSeqElem( circles, i );  
cvCircle( frame, cvPoint(cvRound(p\[0\]),cvRound(p\[1\])), 3, CV\_RGB(0,255,0), -1, 8, 0 );  
cvCircle( frame, cvPoint(cvRound(p\[0\]),cvRound(p\[1\])), cvRound(p\[2\]), CV\_RGB(255,0,0), 3, 8, 0 );  
\}  
  
  
  
  
//阈值分割  
//在G通道下去掉地板  
//在B通道下去掉白色的物体  
//两个分割后的二值图进行与操作，确定网球  
cvThreshold(G\_part,G\_part, 190, 255,CV\_THRESH\_BINARY);  
cvCopy(G\_part,biImage,NULL);//测试中间结果  
cvThreshold(B\_part, B\_part,145,255,CV\_THRESH\_BINARY\_INV);  
   
  
  
      
  
  
  
  
//获取并绘制轮廓  
//将两个阈值分割的图片进行与操作，赋值给G通道  
cvAnd(G\_part, B\_part,G\_part,NULL);  
  
  
//对分割得到的网球进行适当腐蚀和膨胀  
cvErode(G\_part, G\_part,NULL,1);  
cvDilate(G\_part,G\_part,NULL,9);  
  
//找到轮廓并绘制  
cvFindContours( G\_part, storage, &contour, sizeof(CvContour), CV\_RETR\_CCOMP, CV\_CHAIN\_APPROX\_SIMPLE );  
cvZero( dst );  
for( ; contour != 0; contour = contour->h\_next)  
\{  
  
  
contourRect = cvBoundingRect(contour,0);  
  
  
if((contourRect.width > 60) &&(contourRect.height >60))\{  
CvScalar color = CV\_RGB( rand()&255, rand()&255, rand()&255 );//每次都随机颜色显示  
/\* 用1替代 CV\_FILLED  所指示的轮廓外形 \*/  
cvDrawContours( dst, contour, color, color, -1, CV\_FILLED, 8 );  
  
//绘制找到的轮廓的矩形框  
cvRectangle(dst ,cvPoint(contourRect.x, contourRect.y),  
cvPoint(contourRect.x + contourRect.width, contourRect.y + contourRect.height),  
CV\_RGB(255,0,0),  
1,  
8,  
0);  
\}  
   
\}  
    
   //显示各个计算出的图像，包括中间运算结果  
cvShowImage("Camera", frame);    
cvShowImage( "contours", dst );  
cvShowImage("B\_channel",B\_part);  
cvShowImage("G\_channel", G\_part);  
cvShowImage("R\_channel",R\_part);  
cvShowImage("biImage",biImage);  
cvShowImage("biImage\_B",biImage\_B);  
  
  
  
  
int key1;  
key1 = cvWaitKey (300);  
if (key1 == 'q' || key1 == 'Q')    
break;    
  
  
  
\}  
count++;  
\}     
  
  
  
  
cvReleaseCapture(&pCapture);    //销毁摄像头    
  
  
  
cvReleaseImage(&dst);  
cvReleaseImage(&B\_part);  
cvReleaseImage(&G\_part);  
cvReleaseImage(&R\_part);  
cvReleaseImage(&biImage);  
cvReleaseImage(&biImage\_B);  
  
  
cvDestroyWindow("Camera");  //销毁窗口   
cvDestroyWindow("contours");  
cvDestroyWindow("B\_channel");  
cvDestroyWindow("G\_channel");  
cvDestroyWindow("R\_channel");  
cvDestroyWindow("circle");  
cvDestroyWindow("biImage");  
cvDestroyWindow("biImage\_B");  
\}  
  
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[0_1317384061eEEI.gif]: /images/20220618/cecb736ee5004af2bbfd8b5d6d80214e.png