用c++写一个cvSnakeImage的例子
时间: 2024-05-17 12:18:06 浏览: 13
cvSnakeImage是OpenCV中实现贪婪算法的函数,可以用于图像分割等领域。以下是一个用C++编写的cvSnakeImage的例子:
```c++
#include <opencv2/opencv.hpp>
#include <iostream>
using namespace cv;
using namespace std;
int main(int argc, char** argv)
{
Mat image = imread("test.jpg");
if (image.empty())
{
cout << "Could not open or find the image" << endl;
return -1;
}
namedWindow("Original Image", WINDOW_NORMAL);
imshow("Original Image", image);
Mat gray, blur, edges;
cvtColor(image, gray, COLOR_BGR2GRAY);
GaussianBlur(gray, blur, Size(3, 3), 0);
Canny(blur, edges, 50, 150);
namedWindow("Edges", WINDOW_NORMAL);
imshow("Edges", edges);
vector<Point> points;
points.push_back(Point(50, 50));
points.push_back(Point(200, 50));
points.push_back(Point(200, 200));
points.push_back(Point(50, 200));
vector<Point> snake;
snake = points;
int iterations = 100;
int alpha = 1;
int beta = 1;
int gamma = 1;
cvSnakeImage(edges, snake, &alpha, &beta, &gamma, CV_CALIB_CB_ADAPTIVE_THRESH, Size(3, 3), TermCriteria(TermCriteria::COUNT + TermCriteria::EPS, iterations, 0.01));
for (size_t i = 0; i < snake.size(); i++)
{
circle(image, snake[i], 2, Scalar(0, 0, 255), -1);
}
namedWindow("Snake", WINDOW_NORMAL);
imshow("Snake", image);
waitKey(0);
return 0;
}
```
这个例子中,我们首先读入一张图片,然后将其转换为灰度图像并进行高斯模糊和Canny边缘检测。接着,我们定义一组点并将其作为初始的贪婪算法的轮廓。然后,我们设置贪婪算法的参数,包括迭代次数、alpha、beta和gamma等参数。最后,我们调用cvSnakeImage函数对图像进行分割,并将分割结果绘制在原图上,最终显示出来。