基于距离变换与分水岭的图像分割 (二)

增加了标记,分水岭变换与着色,着色中的轮廓填充判定条件可以仔细看一下,下面是分水岭分割完整代码

#include"pch.h"
#include<iostream>
#include<opencv2/opencv.hpp>
#include<math.h>
using namespace std;
using namespace cv;

int main(int argc, char** argv)
{
    Mat src,gray;
    src = imread("water.jpg");
    imshow("input img", src);
    //cvtColor(src, gray, COLOR_BGR2GRAY);
    //反转背景
    for(int row=0;row<src.rows;++row)
        for (int col = 0; col < src.cols; ++col)
        {
            if (src.at<Vec3b>(row, col) == Vec3b(255, 255, 255))
            {
                src.at<Vec3b>(row, col)[0] = 0;
                src.at<Vec3b>(row, col)[1] = 0;
                src.at<Vec3b>(row, col)[2] = 0;
            }
        }
    imshow("black background", src);


    //锐化
    Mat imgLaplance;
    Mat sharp = src;
    src.convertTo(sharp, CV_32F);
    Mat kernel = (Mat_<float>(3, 3) << 1, 1, 1, 1, -8, 1, 1, 1, 1);
    filter2D(src, imgLaplance, CV_32F, kernel, Point(-1, -1), 0, BORDER_DEFAULT);
    Mat resultImg = sharp - imgLaplance;

    resultImg.convertTo(resultImg, CV_8UC3);
    imgLaplance.convertTo(imgLaplance, CV_8UC3);
    imshow("sharp", resultImg);


    //二值距离变换
    Mat binaryImg;
    cvtColor(resultImg, resultImg, COLOR_BGR2GRAY);
    threshold(resultImg, binaryImg, 40, 255, THRESH_BINARY | THRESH_OTSU);
    imshow("binary", binaryImg);

    //距离变换
    Mat dstImg;
    distanceTransform(binaryImg, dstImg, DIST_L1, 3, 5);
    normalize(dstImg, dstImg, 0, 1, NORM_MINMAX);
    imshow("dist img", dstImg);
    threshold(dstImg, dstImg, 0.4, 1, THRESH_BINARY);
    imshow("threshold", dstImg);

    //二值腐蚀
    Mat Kernel1 = Mat::ones(13,13, CV_8UC1);
    erode(dstImg, dstImg, Kernel1, Point(-1, -1));
    imshow("erode", dstImg);

    //标记
    Mat dist_8u;
    dstImg.convertTo(dist_8u, CV_8U);
    vector<vector<Point>> contours;
    findContours(dist_8u, contours, RETR_EXTERNAL, CHAIN_APPROX_SIMPLE, Point(0, 0));
    Mat markers = Mat::zeros(src.size(), CV_32SC1);
    for(size_t i=0;i<contours.size();++i)
    { 
        drawContours(markers, contours, static_cast<int>(i), Scalar::all(static_cast<int>(i) + 1),-1);
    }
    circle(markers, Point(5, 5), 3, Scalar(255, 255, 255), -1);
    imshow("markers", markers * 1000);

    //分水岭变换
    watershed(src, markers);
    Mat mark = Mat::zeros(markers.size(), CV_8UC1);
    markers.convertTo(mark, CV_8UC1);
    bitwise_not(mark, mark, Mat());
    imshow("watershold", mark);

    //着色
    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));
    }

    Mat dst = Mat::zeros(markers.size(), CV_8UC3);
    for(int row=0;row<markers.rows;++row)
        for (int col = 0; col < markers.cols; ++col)
        {
            int index = markers.at<int>(row, col);
            if (index > 0 && index <= static_cast<int>(contours.size()))
                dst.at<Vec3b>(row, col) = colors[index - 1];
            else
                dst.at<Vec3b>(row, col) = Vec3b(0, 0, 0);
        }

    imshow("final rslt", dst);
    waitKey();
    return 0;
}

基于距离变换与分水岭的图像分割 (二)

 

 基于距离变换与分水岭的图像分割 (二)

 

 基于距离变换与分水岭的图像分割 (二)

 

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