opencv 查找连通区域 最大面积

• 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 
#include 

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 > 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)
{
   /*
    vector > contours; // Vector for storing contours
    
    int largest_area=0;
    size_t largest_contour_index=0;
    Rect bounding_rect;
    
    findContours( srcImage, 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
        }
    }
    
    Mat dst;
    cvtColor(srcImage, dst, CV_GRAY2RGB);
    drawContours( dst, contours,largest_contour_index, Scalar( 0, 255, 0 ), 2 ); // Draw the largest contour using previously stored index.
    imshow( "result", dst );
    waitKey();
    
    printf("%%%%%%%%%%%max area:%d\n", largest_area);
    return make_pair( largest_area, 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 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(label,cv::CC_STAT_LEFT) << std::endl;
        std::cout << "CC_STAT_TOP    = " << stats.at(label,cv::CC_STAT_TOP) << std::endl;
        std::cout << "CC_STAT_WIDTH  = " << stats.at(label,cv::CC_STAT_WIDTH) << std::endl;
        std::cout << "CC_STAT_HEIGHT = " << stats.at(label,cv::CC_STAT_HEIGHT) << std::endl;
        std::cout << "CC_STAT_AREA   = " << stats.at(label,cv::CC_STAT_AREA) << std::endl;
        std::cout << "CENTER   = (" << centroids.at(label, 0) <<","<< centroids.at(label, 1) << ")"<< std::endl << std::endl;
        
        int area = stats.at(label,cv::CC_STAT_AREA);
        int left =  stats.at(label,cv::CC_STAT_LEFT);
        int top = stats.at(label,cv::CC_STAT_TOP);
        int width = stats.at(label,cv::CC_STAT_WIDTH);
        int height = stats.at(label,cv::CC_STAT_HEIGHT);
        
        vec_area.push_back(area);
        vec_width.push_back(width);
        vec_height.push_back(height);
    }
    
    vector::iterator bigwidth = std::max_element(std::begin(vec_width), std::end(vec_width));
    vector::iterator bigheight = std::max_element(std::begin(vec_height), std::end(vec_height));
    vector::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(y, x);
            CV_Assert(0 <= label && label <= nccomps);
            img_color.at(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。