分水嶺方法是基於影象形態學，影象結構，來進行分割的一種方法

演算法實現方式：
    - 基於浸泡理論的分水嶺分割方法
    - 基於連通圖的方法
    - 基於距離變換的方法(opencv中依此實現)

基於距離的分水嶺分割流程：

程式碼： 粘連物件分離與計數

    #include "../common/common.hpp"

    void main(int argc, char** argv) 
    {
        Mat src = imread(getCVImagesPath("images/coins_001.jpg"));
        imshow("src5-7", src);

        Mat gray, binary, shifted;
        // 將灰度值相近的元素進行聚類，將顏色資料差距不大的畫素點合成一個顏色，方便後續處理
        pyrMeanShiftFiltering(src, shifted, 21, 51); // 去邊緣保留濾波，引數：輸入影象，輸出影象，空間窗的半徑，色彩窗的半徑
        imshow("shifted", shifted);

        cvtColor(shifted, gray, COLOR_BGR2GRAY);
        threshold(gray, binary, 0, 255, THRESH_BINARY | THRESH_OTSU);
        imshow("binary", binary);

        // distance transform
        Mat dist;
        distanceTransform(binary, dist, DistanceTypes::DIST_L2, 3, CV_32F);
        normalize(dist, dist, 0, 1, NORM_MINMAX);
        imshow("distance result", dist);

        // binary
        threshold(dist, dist, 0.4, 1, THRESH_BINARY);
        imshow("distance binary", dist);

        // 發現輪廓
        Mat dist_m;
        dist.convertTo(dist_m, CV_8U);
        vector<vector<Point>> contours;
        findContours(dist_m, contours, RETR_EXTERNAL, CHAIN_APPROX_SIMPLE, Point(0, 0));

        // create markers
        Mat markers = Mat::zeros(src.size(), CV_32SC1); // 如果使用 CV_8UC1 ，watershed 函式會報錯
        for (size_t t = 0; t < contours.size(); t++) {
            drawContours(markers, contours, static_cast<int>(t), Scalar::all(static_cast<int>(t) + 1), -1);
        }
        circle(markers, Point(5, 5), 3, Scalar(255), -1); // 建立marker，標記的位置如果在要分割的影象塊上會影響分割的結果，如果不建立，分水嶺變換會無效
        imshow("markers", markers*10000);

        // 形態學操作 - 彩色影象，目的是去掉干擾，讓結果更好
        Mat k = getStructuringElement(MORPH_RECT, Size(3, 3), Point(-1, -1));
        morphologyEx(src, src, MORPH_ERODE, k); // 腐蝕，去粘連部位的干擾

        // 完成分水嶺變換
        watershed(src, markers);
        Mat mark = Mat::zeros(markers.size(), CV_8UC1);
        markers.convertTo(mark, CV_8UC1);
        bitwise_not(mark, mark, Mat());
        imshow("watershed result", mark);

        // generate random color
        vector<Vec3b> colors;
        for (size_t i = 0; i < contours.size(); i++) {
            int r = theRNG().uniform(0, 255);
            int g = theRNG().uniform(0, 255);
            int b = theRNG().uniform(0, 255);
            colors.push_back(Vec3b((uchar)b, (uchar)g, (uchar)r));
        }

        // 顏色填充與最終顯示
        Mat dst = Mat::zeros(markers.size(), CV_8UC3);
        int index = 0;
        for (int row = 0; row < markers.rows; row++) {
            for (int col = 0; col < markers.cols; col++) {
                index = markers.at<int>(row, col);
                if (index > 0 && index <= contours.size()) {
                    dst.at<Vec3b>(row, col) = colors[index - 1];
                }
                else {
                    dst.at<Vec3b>(row, col) = Vec3b(0, 0, 0);
                }
            }
        }
        imshow("ret5-7", dst);
        printf("number of objects : %d\n", contours.size());

        waitKey(0);
    }
 

效果圖

程式碼： 影象分割

    #include "../common/common.hpp"

    static Mat * watershedCluster(Mat &image, int &numSegments);
    static void createDisplaySegments(Mat &segments, int numSegments, Mat &image);

    void main(int argc, char** argv) 
    {
        Mat src = imread(getCVImagesPath("images/toux.jpg"));
        imshow("src5-10", src);

        int numSegments;
        Mat * markers = watershedCluster(src, numSegments);
        createDisplaySegments(*markers, numSegments, src);
        waitKey(0);
        delete markers;
    }

    Mat * watershedCluster(Mat &image, int &numComp) // 完成分水嶺變換，並返回輪廓的數目
    {
        // 二值化
        Mat gray, binary;
        cvtColor(image, gray, COLOR_BGR2GRAY);
        threshold(gray, binary, 0, 255, THRESH_BINARY | THRESH_OTSU);
        // 形態學與距離變換
        Mat k = getStructuringElement(MORPH_RECT, Size(3, 3), Point(-1, -1));
        morphologyEx(binary, binary, MORPH_OPEN, k, Point(-1, -1)); // 去掉小的點的干擾，分水嶺分割是自動計算分類，如果有干擾，分類就會有很多
        Mat dist;
        distanceTransform(binary, dist, DistanceTypes::DIST_L2, 3, CV_32F);
        normalize(dist, dist, 0.0, 1.0, NORM_MINMAX);

        // 開始生成標記
        threshold(dist, dist, 0.1, 1.0, THRESH_BINARY);
        normalize(dist, dist, 0, 255, NORM_MINMAX);
        dist.convertTo(dist, CV_8UC1);

        // 標記開始
        vector<vector<Point>> contours;
        vector<Vec4i> hireachy;
        findContours(dist, contours, hireachy, RETR_CCOMP, CHAIN_APPROX_SIMPLE);
        if (contours.empty()) return NULL;

        //Mat markers(dist.size(), CV_32S); // 如果使用 CV_8UC1 ，watershed 函式會報錯
        Mat * markers = new Mat(dist.size(), CV_32S); // 如果使用 CV_8UC1 ，watershed 函式會報錯
        *markers = Scalar::all(0);
        for (int i = 0; i < contours.size(); i++) 
        {
            drawContours(*markers, contours, i, Scalar(i + 1), -1, 8, hireachy, INT_MAX);
        }
        circle(*markers, Point(5, 5), 3, Scalar(255), -1); // 建立標記

        // 分水嶺變換
        watershed(image, *markers);
        numComp = contours.size();
        return markers;
    }

    void createDisplaySegments(Mat &markers, int numSegments, Mat &image) 
    {
        // generate random color
        vector<Vec3b> colors;
        for (size_t i = 0; i < numSegments; i++) 
        {
            int r = theRNG().uniform(0, 255);
            int g = theRNG().uniform(0, 255);
            int b = theRNG().uniform(0, 255);
            colors.push_back(Vec3b((uchar)b, (uchar)g, (uchar)r));
        }

        // 顏色填充與最終顯示
        Mat dst = Mat::zeros(markers.size(), CV_8UC3);
        int index = 0;
        for (int row = 0; row < markers.rows; row++) 
        {
            for (int col = 0; col < markers.cols; col++) 
            {
                index = markers.at<int>(row, col);
                if (index > 0 && index <= numSegments) 
                {
                    dst.at<Vec3b>(row, col) = colors[index - 1];
                }
                else 
                {
                    dst.at<Vec3b>(row, col) = Vec3b(255, 255, 255);
                }
            }
        }
        imshow("watershed5-10", dst);
    }
 

效果圖