two Pass方法连通域检测

原理：

Two-Pass方法检测连通域的原理可参见这篇博客：http://blog.csdn.net/lichengyu/article/details/13986521。

参考下面动图，一目了然。

代码：

代码中标记图的数据类型要注意，如果first pass中标记数多于255，就不要用uchar类型，我直接设置为int类型。

 #include "opencv2/imgproc/imgproc.hpp"
 #include "opencv2/highgui/highgui.hpp"
 #include <map>
 #include <cassert>
 #include <iostream>

 using namespace std;

 const int max_size = ;
 int parent[max_size] = {  };

 // 找到label x的根节点
 int Find(int x, int parent[])
 {
     assert(x < max_size);
     int i = x;
     while ( != parent[i])
         i = parent[i];
     return i;
 }

 // 将label x 和 label y合并到同一个连通域
 void Union(int x, int y, int parent[])
 {
     assert(x < max_size && y < max_size);
     int i = x;
     int j = y;
     while ( != parent[i])
         i = parent[i];
     while ( != parent[j])
         j = parent[j];
     if (i != j)
         parent[i] = j;
 }

 cv::Mat twoPassConnectComponent(cv::Mat &binaryImg)
 {
     int imgW = binaryImg.cols;
     int imgH = binaryImg.rows;
     int channel = binaryImg.channels();
     int type = binaryImg.type();
     // first pass
     int label = ;

     cv::Mat dst = cv::Mat::zeros(cv::Size(imgW, imgH), CV_32SC1);
     for (int y = ; y < imgH; y++)
     {
         for (int x = ; x < imgW; x++)
         {
             if (binaryImg.at<uchar>(y, x) != )
             {
                 int left = (x -  < ) ?  : dst.at<int>(y, x - );
                 int up = (y -  < ) ?  : dst.at<int>(y - , x);

                 if (left !=  || up != )
                 {
                     if (left !=  && up != )
                     {
                         dst.at<int>(y, x) = min(left, up);
                         if (left <= up)
                             Union(up, left, parent);
                         else if (up<left)
                             Union(left, up, parent);
                     }
                     else
                         dst.at<int>(y, x) = max(left, up);
                 }
                 else
                 {
                     dst.at<int>(y, x) = ++label;
                 }
             }
         }
     }

     //second pass
     for (int y = ; y < imgH; y++)
     {
         for (int x = ; x < imgW; x++)
         {
             if (binaryImg.at<uchar>(y, x) != )
                 dst.at<int>(y, x) = Find(dst.at<int>(y, x), parent);
         }
     }

     return dst;
 }

 cv::Scalar getRandomColor()
 {
     uchar r =  * (rand() / (1.0 + RAND_MAX));
     uchar g =  * (rand() / (1.0 + RAND_MAX));
     uchar b =  * (rand() / (1.0 + RAND_MAX));
     return cv::Scalar(b, g, r);
 }

 cv::Mat showColorLabel(cv::Mat label)
 {
     int imgW = label.cols;
     int imgH = label.rows;
     std::map<int, cv::Scalar> colors;

     cv::Mat colorLabel = cv::Mat::zeros(imgH, imgW, CV_8UC3);
     int *pLabel = (int*)label.data;
     uchar *pColorLabel = colorLabel.data;
     for (int i = ; i < imgH; i++)
     {
         for (int j = ; j < imgW; j++)
         {
             int idx = (i*imgW + j) * ;
             int pixelValue = pLabel[i*imgW + j];
             if (pixelValue > )
             {
                 if (colors.count(pixelValue) <= )
                 {
                     colors[pixelValue] = getRandomColor();
                 }
                 cv::Scalar color = colors[pixelValue];
                 pColorLabel[idx + ] = color[];
                 pColorLabel[idx + ] = color[];
                 pColorLabel[idx + ] = color[];
             }
         }
     }

     return colorLabel;
 }

 int main()
 {
     // 加载图像
     string imageName = "data/source_images/logo.png";
     cv::Mat image = cv::imread(imageName, );
     if (!image.data)
     {
         cout << "No image data" << endl;
         getchar();
         return -;
     }
     //转为灰度图
     cv::cvtColor(image, image, CV_RGB2GRAY);
     //阈值化，情景为255，背景为0
     cv::Mat threshImg;
     cv::threshold(image, threshImg, , , cv::THRESH_BINARY);
     cv::bitwise_not(threshImg, threshImg);

     //连通域检测 two Pass方法标记图像
     cv::Mat labelImg = twoPassConnectComponent(threshImg);

     //不同连通区域用不同颜色表示
     cv::Mat colorLabelImg=showColorLabel(labelImg);

     //显示
     cv::imshow("thresh", threshImg);
     cv::imshow("label", labelImg*);
     cv::imshow("colorLabel", colorLabelImg);
     cv::waitKey();
 }

结果：

使用OpenCV的logo为素材图，如下：

（1）转为灰度图然后阈值化

（2）寻找连通域

（3）不同连通区域不同颜色显示

   

   

封装后的代码见我的码云code：https://gitee.com/rxdj/twoPassMethod.git