#include <opencv2/opencv.hpp>
#include <iostream>
int main(int argc, char** argv){
char intput_win[] = "input image";
char watershed_win[] = "watershed segmentation demo";
cv::Mat src = cv::imread("../../source/segmetation_1.png");
if(src.empty()){
std::cout << "could not load image..." << std::endl;
return -1;
}
cv::namedWindow(intput_win);
cv::imshow(intput_win, src);
for(int row = 0; row < src.rows; row++){
for(int col = 0; col < src.cols; col++){
if(src.at<cv::Vec3b>(row, col) == cv::Vec3b(255, 255, 255)){
src.at<cv::Vec3b>(row, col)[0] = 0;
src.at<cv::Vec3b>(row, col)[1] = 0;
src.at<cv::Vec3b>(row, col)[2] = 0;
}
}
}
cv::namedWindow("black background");
cv::imshow("black background", src);
// sharpen
cv::Mat kernel = (cv::Mat_<float>(3, 3) << 1, 1, 1, 1, -8, 1, 1, 1, 1);
cv::Mat imgLaplance;
cv::filter2D(src, imgLaplance, CV_32F, kernel);
cv::Mat sharpenImg;
src.convertTo(sharpenImg, CV_32F);
cv::Mat resultImg = sharpenImg - imgLaplance;
imgLaplance.convertTo(imgLaplance, CV_8UC3);
cv::imshow("imgLaplance image", imgLaplance);
resultImg.convertTo(resultImg, CV_8UC3);
cv::imshow("sharpen image", resultImg);
src = resultImg;
// convert to binary
cv::Mat binaryImg;
cv::cvtColor(resultImg, resultImg, cv::COLOR_BGR2GRAY);
cv::threshold(resultImg, binaryImg, 40, 255, cv::THRESH_BINARY | cv::THRESH_OTSU);
cv::imshow("binary image", binaryImg);
cv::Mat distImg;
cv::distanceTransform(binaryImg, distImg, cv::DIST_L1, 3, 5);
cv::normalize(distImg, distImg, 0, 1, cv::NORM_MINMAX);
cv::imshow("distance result", distImg);
// binary again
cv::threshold(distImg, distImg, 0.4, 1, cv::THRESH_BINARY);
cv::imshow("distance binary result", distImg);
cv::Mat k1 = cv::Mat::ones(5, 5, CV_8UC1);
cv:erode(distImg, distImg, k1);
cv::imshow("erode image", distImg);
// markers
cv::Mat dist_8u;
distImg.convertTo(dist_8u, CV_8U);
std::vector<std::vector<cv::Point>> contours;
cv::findContours(dist_8u, contours, cv::RETR_EXTERNAL, cv::CHAIN_APPROX_SIMPLE);
cv::Mat markers = cv::Mat::zeros(src.size(), CV_32SC1);
for(size_t i = 0; i < contours.size(); i++){
cv::drawContours(markers, contours, static_cast<int>(i), cv::Scalar::all(static_cast<int>(i) + 1), -1);
}
markers.convertTo(markers, CV_8UC3);
// cv::circle(markers, cv::Point(5, 5), 3, cv::Scalar(255, 255, 255), -1);
cv::imshow("my markers", markers * 1000);
// perform watershed
markers.convertTo(markers, CV_32SC1);
cv::watershed(src, markers);
cv::Mat mark = cv::Mat::zeros(markers.size(), CV_8UC1);
markers.convertTo(mark, CV_8UC1);
cv::bitwise_not(mark, mark);
cv::imshow("watershed image", mark);
// generate random color
std::vector<cv::Vec3b> colors;
for(size_t i = 0; i < contours.size(); i++){
int r = cv::theRNG().uniform(0, 255);
int g = cv::theRNG().uniform(0, 255);
int b = cv::theRNG().uniform(0, 255);
colors.push_back(cv::Vec3b((uchar)b, (uchar)g, (uchar)r));
}
// fill with color and display final result
cv::Mat dst = cv::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<cv::Vec3b>(row, col) = colors[index - 1];
}
else{
dst.at<cv::Vec3b>(row, col) = cv::Vec3b(0, 0, 0);
}
}
}
imshow("Final Result", dst);
cv::waitKey();
}
32.基于距离变换和分水岭的图像分割
最新推荐文章于 2024-02-01 18:09:19 发布