test9.zip_opencv 寻找mark_opencv 椭圆检测_opencv圆形 拟合_site:www.pudn.co

#include <iostream> #include <opencv2/core/core.hpp> #include <opencv2/highgui/highgui.hpp> #include <highgui.h> #include<opencv2/imgproc/imgproc.hpp> #include "cv.h" using namespace cv; using namespace std; Mat g_cannyMat_output; vector<vector<Point>> g_vContours; vector<Vec4i> g_vHierarchy; double minArea=30; double maxArea=800; double minLen=50; double maxLen=200; int slider_pos=70;//阈值 Mat dstImage,edge,grayImage,image0; //参数定义 void process_image(int h); int main() { Mat srcImage=imread("filename.jpg");//载入原图像 cvNamedWindow("image"); imshow("image", srcImage); //显示图像 //【2】将原图像转换为灰度图像 cvtColor( srcImage, grayImage, COLOR_BGR2GRAY ); imshow("【效果图】灰度", grayImage); //【3】先用使用 3x3内核来降噪 blur( grayImage, edge, Size(3,3) ); imshow("【效果图】模糊", edge); //【4】运行Canny算子 Canny( edge, edge, 35, 115,3 ); //【5】显示效果图 imshow("【效果图】Canny边缘检测", edge); //将最高阈值为最低阈值的三倍 process_image(0); waitKey(0); } void process_image(int h) { CvMemStorage *stor; CvSeq *cont; CvPoint *PointArray; stor = cvCreateMemStorage(0); cont = cvCreateSeq(CV_SEQ_ELTYPE_POINT,sizeof(CvSeq),sizeof(CvPoint),stor); int count= cont->total;//轮廓个数 threshold(edge,dstImage,slider_pos,255,CV_THRESH_BINARY); findContours( dstImage, g_vContours, g_vHierarchy, RETR_TREE, CHAIN_APPROX_SIMPLE, Point(0, 0) ); //cvFindContours(dstImage,stor,&cont,sizeof(CvContour),CV_RETR_LIST,CV_CHAIN_APPROX_NONE,cvPoint(0,0)); // 计算矩 vector<Moments> mu(g_vContours.size() ); for(unsigned int i = 0; i < g_vContours.size(); i++ ) { mu[i] = moments( g_vContours[i], false ); } // 计算中心矩 vector<Point2f> mc( g_vContours.size() ); for( unsigned int i = 0; i < g_vContours.size(); i++ ) { mc[i] = Point2f( static_cast<float>(mu[i].m10/mu[i].m00), static_cast<float>(mu[i].m01/mu[i].m00 )); } Mat drawing = Mat::zeros( dstImage.size(), CV_8UC3 ); //绘制轮廓并用椭圆拟合 for( unsigned int i = 0; i< g_vContours.size(); i++ ) { double a = abs(contourArea(g_vContours[i]) ) ; //求轮廓面积 double b = abs(arcLength(g_vContours[i], true) ) ; //求轮廓长度 if( a>= minArea&&a<= maxArea&& b>= minLen&&b<= maxLen) //进行几何 束，面积阈值设置为1到800,长度阈值设置为5到 20 { drawContours( drawing, g_vContours, i, Scalar(255,129,0), 2, 8, g_vHierarchy, 0, Point() ); //得到点集（这个方法值得借鉴） //cvCvtSeqToArray(cont,PointArray,CV_WHOLE_SEQ); ////拟合当前轮廓 //fitEllipse(count); //画椭圆 circle( drawing, mc[i], 4, Scalar(255,129,0), -1, 8, 0 ); } /*ellipse(drawing,center,size,0,0,360,Scalar(255,129,0),1,8); */ } imshow("Result",drawing); }