opencv的分水岭算法的输入是包含一个轮廓的mask。
Mat src = imread("C:/opencv/data/coins.jpg");
// Mat src = imread("D:/kuaidi.jpg");
if (src.empty()) {
printf("could not load image...\n");
return -1;
}
Mat binaryImg;
Mat grayImg;
cvtColor(src, grayImg, CV_BGR2GRAY);
threshold(grayImg, binaryImg, 40, 255, THRESH_BINARY);
Mat k1 = Mat::ones(9, 9, CV_8UC1);
erode(binaryImg, binaryImg, k1, Point(-1, -1), 2);
Mat dist_8u;
binaryImg.convertTo(dist_8u, CV_8U);
vector> contours;
findContours(dist_8u, contours, RETR_EXTERNAL, CHAIN_APPROX_SIMPLE, Point(0, 0));
// create makers
Mat markers = Mat::zeros(src.size(), CV_32SC1);
for (size_t i = 0; i < contours.size(); i++) {
drawContours(markers, contours, static_cast(i), Scalar::all(static_cast(i) + 1), -1);
}
circle(markers, Point(5, 5), 3, Scalar(255, 255, 255), -1);
watershed(src, markers);
Mat mark = Mat::zeros(markers.size(), CV_8UC1);
markers.convertTo(mark, CV_8UC1);
bitwise_not(mark, mark, Mat());
imshow("watershed image", mark);
vector 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));
}
// fill with color and display final result
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(row, col);
if (index > 0 && index <= static_cast(contours.size())) {
dst.at(row, col) = colors[index - 1];
}
else {
dst.at(row, col) = Vec3b(0, 0, 0);
}
}
}
虽然9块硬币都分割出来了,但是感觉总体效果不是太好,希望有大神能帮忙指导一下。
我看网上有些大神会加入距离变换进来,我尝试了一下,会丢失一个硬币。
Mat distImg;
distanceTransform(binaryImg, distImg, DIST_L1, 3, 5);
normalize(distImg, distImg, 0, 1, NORM_MINMAX);
#include
#include
#include
using namespace std;
using namespace cv;
int main(int argc, char** argv) {
char input_win[] = "input image";
char watershed_win[] = "watershed segmentation demo";
Mat src = imread("C:/opencv/data/coins.jpg");
// Mat src = imread("D:/kuaidi.jpg");
if (src.empty()) {
printf("could not load image...\n");
return -1;
}
namedWindow(input_win, CV_WINDOW_AUTOSIZE);
imshow(input_win, src);
Mat binaryImg;
Mat grayImg;
cvtColor(src, grayImg, CV_BGR2GRAY);
threshold(grayImg, binaryImg, 40, 255, THRESH_BINARY);
Mat k1 = Mat::ones(9, 9, CV_8UC1);
erode(binaryImg, binaryImg, k1, Point(-1, -1), 2);
imwrite("binaryImg.jpg", binaryImg);
Mat dist_8u;
binaryImg.convertTo(dist_8u, CV_8U);
vector> contours;
findContours(dist_8u, contours, RETR_EXTERNAL, CHAIN_APPROX_SIMPLE, Point(0, 0));
// create makers
Mat markers = Mat::zeros(src.size(), CV_32SC1);
for (size_t i = 0; i < contours.size(); i++) {
drawContours(markers, contours, static_cast(i), Scalar::all(static_cast(i) + 1), -1);
}
circle(markers, Point(5, 5), 3, Scalar(255, 255, 255), -1);
imshow("my markers", markers * 1000);
imwrite("my_markers.jpg", markers);
// perform watershed
watershed(src, markers);
Mat mark = Mat::zeros(markers.size(), CV_8UC1);
markers.convertTo(mark, CV_8UC1);
bitwise_not(mark, mark, Mat());
imshow("watershed image", mark);
imwrite("watershed_image.jpg", mark);
// generate random color
vector 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));
}
// fill with color and display final result
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(row, col);
if (index > 0 && index <= static_cast(contours.size())) {
dst.at(row, col) = colors[index - 1];
}
else {
dst.at(row, col) = Vec3b(0, 0, 0);
}
}
}
imshow("Final Result", dst);
imwrite("Final_Result.jpg", dst);
waitKey(0);
return 0;
}