OpenCV 圆与矩形识别的方法

HoughCircles(edges, circles, CV_HOUGH_GRADIENT, 1.5, 10, 200, 100, 0, 0);

cvThreshold(tgray, gray, 75, 250, CV_THRESH_BINARY);

#include  
#include  
#include 
#include
#include
#include 
#include 
#include
#include 
#pragma comment(lib,"ws2_32.lib")
#include
 
using namespace cv;
 
 
   //////////////////////////////////////////////////////////////////
   //函数功能：用向量来做COSα=两向量之积/两向量模的乘积求两条线段夹角
   //输入：  线段3个点坐标pt1,pt2,pt0,最后一个参数为公共点
   //输出：  线段夹角，单位为角度
   //////////////////////////////////////////////////////////////////
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;
 double angle_line = (dx1*dx2 + dy1 * dy2) / sqrt((dx1*dx1 + dy1 * dy1)*(dx2*dx2 + dy2 * dy2) + 1e-10);//余弦值
 return acos(angle_line) * 180 / 3.141592653;
}
//////////////////////////////////////////////////////////////////
//函数功能：采用多边形检测，通过约束条件寻找矩形
//输入：  img 原图像
//     storage 存储
//     minarea，maxarea 检测矩形的最小/最大面积
//     minangle,maxangle 检测矩形边夹角范围，单位为角度
//输出：  矩形序列
//////////////////////////////////////////////////////////////////
CvSeq* findSquares4(IplImage* img, CvMemStorage* storage, int minarea, int maxarea, int minangle, int maxangle, int(&temp)[30])
{
 CvSeq* contours;//边缘
 int N = 6; //阈值分级
 CvSize sz = cvSize(img->width & -2, img->height & -2);
 IplImage* timg = cvCloneImage(img);//拷贝一次img
 IplImage* gray = cvCreateImage(sz, 8, 1); //img灰度图
 IplImage* pyr = cvCreateImage(cvSize(sz.width / 2, sz.height / 2), 8, 3); //金字塔滤波3通道图像中间变量
 IplImage* tgray = cvCreateImage(sz, 8, 1); ;
 CvSeq* result;
 double s, t;
 int sk = 0;
 CvSeq* squares = cvCreateSeq(0, sizeof(CvSeq), sizeof(CvPoint), storage);
 
 cvSetImageROI(timg, cvRect(0, 0, sz.width, sz.height));
 //金字塔滤波 
 cvPyrDown(timg, pyr, 7);
 cvPyrUp(pyr, timg, 7);
 //在3个通道中寻找矩形 
 for (int c = 0; c < 3; c++) //对3个通道分别进行处理 
 {
 cvSetImageCOI(timg, c + 1);
 cvCopy(timg, tgray, 0); //依次将BGR通道送入tgray     
 for (int l = 0; l < N; l++)
 {
  //不同阈值下二值化
  cvThreshold(tgray, gray, 75, 250, CV_THRESH_BINARY);
  cvShowImage("111", gray);
  cvFindContours(gray, storage, &contours, sizeof(CvContour), CV_RETR_LIST, CV_CHAIN_APPROX_SIMPLE, cvPoint(0, 0));
  while (contours)
  { //多边形逼近       
  result = cvApproxPoly(contours, sizeof(CvContour), storage, CV_POLY_APPROX_DP, cvContourPerimeter(contours)*0.02, 0);
 
  //如果是凸四边形并且面积在范围内 
  if (result->total == 4 && fabs(cvContourArea(result, CV_WHOLE_SEQ)) > minarea && fabs(cvContourArea(result, CV_WHOLE_SEQ)) < maxarea && cvCheckContourConvexity(result))
  {
 
   s = 0;
   //判断每一条边
   for (int i = 0; i < 5; i++)
   {
   if (i >= 2)
   {  //角度      
    t = fabs(angle((CvPoint*)cvGetSeqElem(result, i), (CvPoint*)cvGetSeqElem(result, i - 2), (CvPoint*)cvGetSeqElem(result, i - 1)));
    s = s > t ? s : t;
   }
   }
   //这里的S为直角判定条件 单位为角度
   if (s > minangle && s < maxangle)
   {
   for (int i = 0; i < 4; i++)
    cvSeqPush(squares, (CvPoint*)cvGetSeqElem(result, i));
   CvRect rect = cvBoundingRect(contours, 1);    // 获取矩形边界框 
   CvPoint p1;
   p1 = cvPoint(rect.x + rect.width / 2, rect.y + rect.height / 2);  //矩形中心坐标 
   std::cout << "X:" << p1.x << "Y：" << p1.y << std::endl;
   }
  }
  contours = contours->h_next;
  }
 }
 std::cout << "圆的数量是"<total; i += 4)
 {
 CvPoint* rect = pt;
 int count = 4;
 memcpy(pt, reader.ptr, squares->elem_size);
 CV_NEXT_SEQ_ELEM(squares->elem_size, reader);
 memcpy(pt + 1, reader.ptr, squares->elem_size);
 CV_NEXT_SEQ_ELEM(squares->elem_size, reader);
 memcpy(pt + 2, reader.ptr, squares->elem_size);
 CV_NEXT_SEQ_ELEM(squares->elem_size, reader);
 memcpy(pt + 3, reader.ptr, squares->elem_size);
 CV_NEXT_SEQ_ELEM(squares->elem_size, reader);
 //cvPolyLine( cpy, &rect, &count, 1, 1, CV_RGB(0,255,0), 3, CV_AA, 0 );
 cvPolyLine(cpy, &rect, &count, 1, 1, CV_RGB(rand() & 255, rand() & 255, rand() & 255), 1, CV_AA, 0);//彩色绘制
 }
 cvShowImage("22", cpy);
 cvReleaseImage(&cpy);
}
 
void SendMessageOne()
{
 //开起摄像头
 VideoCapture capture;
 capture.open(0);
 Mat edges; //定义转化的灰度图
 if (!capture.isOpened())
 namedWindow("【效果图】", CV_WINDOW_NORMAL);
 const char* winn = "1111";
 if (!capture.isOpened())
 //namedWindow(winn, CV_WINDOW_NORMAL);
 CvMemStorage* storage = 0;
 CvMemStorage* storage = 0;
 storage = cvCreateMemStorage(0);
 while (1)
 {
 int Y=0, J=0;
 Mat frame;
 capture >> frame;
 IplImage img0 = frame;
 //drawSquares(&img0, findSquares4(&img0, storage, 100, 2000, 80, 100, a), winn);
 //cvClearMemStorage(storage); //清空存储
 Mat E = frame(Range(1, 320), Range(1, 240));
 cvtColor(frame, edges, CV_BGR2GRAY);
 //高斯滤波
 GaussianBlur(edges, edges, Size(7, 7), 2, 2);
 std::vector circles;//存储每个圆的位置信息
      //霍夫圆
 HoughCircles(edges, circles, CV_HOUGH_GRADIENT, 1.5, 10, 100, 100, 0, 50);
 for (size_t i = 0; i < circles.size(); i++)
 {
  Point center(cvRound(circles[i][0]), cvRound(circles[i][1]));
  int radius = cvRound(circles[i][2]);
  //std::cout << "圆的X是" << circles[i][0] << "圆的Y是" << circles[i][1] << std:: endl;
  //绘制圆轮廓 
  circle(frame, center, radius, Scalar(155, 50, 255), 3, 8, 0);
  int R = frame.at(cvRound(circles[i][1]), cvRound(circles[i][0]))[2];//R
  int G = frame.at(cvRound(circles[i][1]), cvRound(circles[i][0]))[1];//G
  int B = frame.at(cvRound(circles[i][1]), cvRound(circles[i][0]))[0];//B
  int num = R + G + B;
  std::cout << "圆心颜色是" << num << std::endl;
        }
 
 imshow("【效果图】", frame);
 waitKey(30);
 }
}
 
int main()
{
 std::thread *a = new std::thread(SendMessageOne);
 a->join();
 
 return 0;
}