使用matlab实现harris
时间: 2023-12-22 15:05:24 浏览: 22
Harris角点检测算法是一种经典的计算机视觉算法,可以用于检测图像中的角点。下面是使用MATLAB实现Harris角点检测算法的步骤:
1. 读取图像并将其转换为灰度图像。
```matlab
img = imread('lena.jpg');
gray = rgb2gray(img);
```
2. 计算图像的梯度。
```matlab
dx = [-1 0 1; -1 0 1; -1 0 1];
dy = dx';
Ix = conv2(double(gray), dx, 'same');
Iy = conv2(double(gray), dy, 'same');
```
3. 计算每个像素的Harris矩阵。
```matlab
sigma = 2;
g = fspecial('gaussian',[5 5],sigma);
Ix2 = conv2(Ix.^2, g, 'same');
Iy2 = conv2(Iy.^2, g, 'same');
Ixy = conv2(Ix.*Iy, g, 'same');
```
4. 计算每个像素的响应值R。
```matlab
k = 0.04;
R = (Ix2.*Iy2 - Ixy.^2) - k*(Ix2 + Iy2).^2;
```
5. 设置阈值并筛选出角点。
```matlab
threshold = 0.01*max(R(:));
[r, c] = find(R > threshold);
```
6. 在图像上标记角点。
```matlab
imshow(img);
hold on;
plot(c, r, 'r*');
```
完整代码如下:
```matlab
img = imread('lena.jpg');
gray = rgb2gray(img);
dx = [-1 0 1; -1 0 1; -1 0 1];
dy = dx';
Ix = conv2(double(gray), dx, 'same');
Iy = conv2(double(gray), dy, 'same');
sigma = 2;
g = fspecial('gaussian',[5 5],sigma);
Ix2 = conv2(Ix.^2, g, 'same');
Iy2 = conv2(Iy.^2, g, 'same');
Ixy = conv2(Ix.*Iy, g, 'same');
k = 0.04;
R = (Ix2.*Iy2 - Ixy.^2) - k*(Ix2 + Iy2).^2;
threshold = 0.01*max(R(:));
[r, c] = find(R > threshold);
imshow(img);
hold on;
plot(c, r, 'r*');
```