原文补充:
#include<opencv2/opencv.hpp> #include<algorithm> #include<iostream> using namespace std; using namespace cv; int main() { cv::Mat src_img, img_bool, labels, stats, centroids, img_color, img_gray; if( (src_img = cv::imread("13.png",0)).empty()) { cout<<"load image error"<<endl; return -1; } cv::threshold(src_img, img_bool, 0, 255, cv::THRESH_OTSU); //连通域计算 int nccomps = cv::connectedComponentsWithStats ( img_bool, //二值图像 labels, //和原图一样大的标记图 stats, //nccomps×5的矩阵 表示每个连通区域的外接矩形和面积(就是pixel的个数) centroids //nccomps×2的矩阵 表示每个连通区域的质心 ); char title[1024]; sprintf(title,"原图中连通区域数:%d\n",nccomps); cv::String num_connect(title); cv::imshow(num_connect, img_bool); //去除过小区域,初始化颜色表 vector<cv::Vec3b> colors(nccomps); colors[0] = cv::Vec3b(0,0,0); // background pixels remain black. for(int i = 1; i < nccomps; i++ ) { colors[i] = cv::Vec3b(rand()%256, rand()%256, rand()%256); //输出每个连通域的像素个数 cout<<stats.at<int>(i, cv::CC_STAT_AREA)<<endl; //去除面积小于20的连通域 if( stats.at<int>(i, cv::CC_STAT_AREA) < 20 ) colors[i] = cv::Vec3b(0,0,0); // small regions are painted with black too. } //按照label值,对不同的连通域进行着色 img_color = cv::Mat::zeros(src_img.size(), CV_8UC3); for( int y = 0; y < img_color.rows; y++ ) for( int x = 0; x < img_color.cols; x++ ) { int label = labels.at<int>(y, x); CV_Assert(0 <= label && label <= nccomps); img_color.at<cv::Vec3b>(y, x) = colors[label]; } //统计降噪后的连通区域 cv::cvtColor(img_color,img_gray,cv::COLOR_BGR2GRAY); cv::threshold(img_gray, img_gray, 1, 255, cv::THRESH_BINARY); nccomps = cv::connectedComponentsWithStats (img_gray, labels,stats,centroids); sprintf(title,"num of connect area after filter:%d\n",nccomps); num_connect = title; namedWindow(num_connect,0); cv::imshow(num_connect, img_color); cv::waitKey(); return 0; }