MATLAB Source Code for Canny Edge Detection Implementation

Below is the MATLAB source code implementing the Canny edge detection algorithm.

```matlab

% Canny Edge Detection Algorithm

function edges = canny_edge_detection(image)

% Convert RGB image to grayscale using rgb2gray function

gray_image = rgb2gray(image);

% Apply Gaussian filtering to reduce noise using imgaussfilt

% Default sigma value smooths the image while preserving edges

blurred_image = imgaussfilt(gray_image);

% Compute image gradient magnitude and direction

% imgradient calculates Sobel gradients for edge strength and orientation

[gradient_magnitude, gradient_direction] = imgradient(blurred_image);

% Apply non-maximum suppression to thin edges

% This step keeps only local maxima in gradient direction

non_max_suppressed = non_maximum_suppression(gradient_magnitude, gradient_direction);

% Dual thresholding to classify strong and weak edges

% Uses hysteresis thresholding to distinguish clear and potential edges

[strong_edges, weak_edges] = thresholding(non_max_suppressed);

% Edge linking connects weak edges to strong edges

% Final step completes edge contours using connectivity analysis

edges = edge_linking(strong_edges, weak_edges);

end

% Non-maximum suppression implementation

function non_max_suppressed = non_maximum_suppression(gradient_magnitude, gradient_direction)

% Implementation of non-maximum suppression algorithm

% Compares each pixel with its neighbors along gradient direction

% Suppresses non-maximum values to achieve single-pixel wide edges

end

% Dual thresholding implementation

function [strong_edges, weak_edges] = thresholding(non_max_suppressed)

% Implementation of hysteresis thresholding algorithm

% Uses high threshold for strong edges and low threshold for weak edges

% Helps in reducing false edges while maintaining connectivity

end

% Edge linking implementation

function edges = edge_linking(strong_edges, weak_edges)

% Implementation of edge linking algorithm

% Connects weak edges to strong edges using 8-connectivity

% Completes broken edge segments for continuous contours

end

```

The above MATLAB source code implements the complete Canny edge detection algorithm. The program includes essential steps: converting the image to grayscale, applying Gaussian filtering for noise reduction, computing image gradients, performing non-maximum suppression to thin edges, applying dual thresholding for edge classification, and finally executing edge linking to connect edge segments. Through these systematic steps, the algorithm effectively extracts accurate and continuous edge information from the input image while maintaining good noise immunity.