canny edge detection in matlab

The Canny edge detection algorithm is a popular method used in computer vision and image processing to detect the edges in an image. MATLAB provides easy-to-use functions for implementing this algorithm.

To apply the Canny edge detection algorithm in MATLAB, follow the steps below:

1. Read the image using the "imread" function:

main.m
img = imread('image.png');
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2. Convert the image to grayscale:

main.m
gray = rgb2gray(img);
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3. Apply Gaussian blur to the image to reduce noise:

main.m
blur = imgaussfilt(gray, 2);
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4. Use the "edge" function to detect edges using the Canny algorithm:

main.m
canny = edge(blur, 'Canny');
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The "edge" function takes two arguments: the input image and the type of edge detection algorithm to use. In this case, we set the second argument to 'Canny' to use the Canny algorithm.

The resulting image will have white pixels at the locations of detected edges and black pixels elsewhere. You can display the result using the "imshow" function:

main.m
imshow(canny);
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Here's the complete code:

main.m
img = imread('image.png');
gray = rgb2gray(img);
blur = imgaussfilt(gray, 2);
canny = edge(blur, 'Canny');
imshow(canny);
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Feel free to adjust the parameters of the functions and experiment with different images to get the desired results.