今天在弄一个查找连通的最大面积的问题。

要把图像弄成黑底，白字，这样才可以正确找到。

然后调用下边的方法：

RETR_CCOMP:提取所有轮廓，并将轮廓组织成双层结构(two-level hierarchy),顶层为连通域的外围边界，次层位内层边界

#include <opencv2/imgproc.hpp>#include <opencv2/highgui.hpp> using namespace cv;using namespace std; int main( int argc, char** argv ){ Mat src = imread( argv[1] ); int largest_area=0; int largest_contour_index=0; Rect bounding_rect; Mat thr; cvtColor( src, thr, COLOR_BGR2GRAY ); //Convert to gray threshold( thr, thr, 125, 255, THRESH_BINARY ); //Threshold the gray bitwise_not(thr,thr); //这里先变反转颜色 vector<vector<Point> > contours; // Vector for storing contours findContours( thr, contours, RETR_CCOMP, CHAIN_APPROX_SIMPLE ); // Find the contours in the image for( size_t i = 0; i< contours.size(); i++ ) // iterate through each contour. { double area = contourArea( contours[i] ); // Find the area of contour if( area > largest_area ) { largest_area = area; largest_contour_index = i; //Store the index of largest contour bounding_rect = boundingRect( contours[i] ); // Find the bounding rectangle for biggest contour } } drawContours( src, contours,largest_contour_index, Scalar( 0, 255, 0 ), 2 ); // Draw the largest contour using previously stored index. imshow( "result", src ); waitKey(); return 0;}

方法二： connectedComponentsWithStats

std::pair< int , int > MaxAreaFromSource(Mat srcImage, Mat &dstImage, int index){ cv::Mat img_bool, labels, stats, centroids, img_color, img_gray; //连通域计算 int nccomps = cv::connectedComponentsWithStats ( srcImage, //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（pixel） centroids //nccomps×2的矩阵 表示每个连通区域的质心 ); //cv::imshow("labels", labels); //cv::waitKey(); vector<cv::Vec3b> colors(nccomps); colors[0] = cv::Vec3b(0,0,0); // background pixels remain black. printf( "index:%d==================\n",index ); vector< int >vec_width,vec_area,vec_height; for(int label = 1; label < nccomps; ++label) { colors[label] = cv::Vec3b( (std::rand()&255), (std::rand()&255), (std::rand()&255) ); std::cout << "Component "<< label << std::endl; std::cout << "CC_STAT_LEFT = " << stats.at<int>(label,cv::CC_STAT_LEFT) << std::endl; std::cout << "CC_STAT_TOP = " << stats.at<int>(label,cv::CC_STAT_TOP) << std::endl; std::cout << "CC_STAT_WIDTH = " << stats.at<int>(label,cv::CC_STAT_WIDTH) << std::endl; std::cout << "CC_STAT_HEIGHT = " << stats.at<int>(label,cv::CC_STAT_HEIGHT) << std::endl; std::cout << "CC_STAT_AREA = " << stats.at<int>(label,cv::CC_STAT_AREA) << std::endl; std::cout << "CENTER = (" << centroids.at<double>(label, 0) <<","<< centroids.at<double>(label, 1) << ")"<< std::endl << std::endl; int area = stats.at<int>(label,cv::CC_STAT_AREA); int left = stats.at<int>(label,cv::CC_STAT_LEFT); int top = stats.at<int>(label,cv::CC_STAT_TOP); int width = stats.at<int>(label,cv::CC_STAT_WIDTH); int height = stats.at<int>(label,cv::CC_STAT_HEIGHT); vec_area.push_back(area); vec_width.push_back(width); vec_height.push_back(height); } vector<int>::iterator bigwidth = std::max_element(std::begin(vec_width), std::end(vec_width)); vector<int>::iterator bigheight = std::max_element(std::begin(vec_height), std::end(vec_height)); vector<int>::iterator bigarea = std::max_element(std::begin(vec_area), std::end(vec_area)); //printf( "area:%d------------width:%d height:%d \n", *bigarea, *bigwidth, *bigheight ); //按照label值，对不同的连通域进行着色 img_color = cv::Mat::zeros(srcImage.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]; } cv::imshow("color", img_color); cv::waitKey(); return make_pair( *bigarea , index );}

我先用这个函数实现了一下，效果正确，还是opencv demo 是正确的，网上找了个例子，害死我了。

说明一下：方法一 比 第二种方法 运行速度快很多哦！ 这一点很重要。

以上这篇opencv 查找连通区域 最大面积实例就是小编分享给大家的全部内容了，希望能给大家一个参考，也希望大家多多支持。