MATLAB Code Implementation for Edge Detection

This project implements edge detection using MATLAB, accompanied by complete source code and sample images. The code performs edge extraction through the following key steps:

1. Image Import: First, load the target image into the MATLAB environment using functions from the Image Processing Toolbox, typically employing imread() function with proper path specification and format validation.

2. Image Preprocessing: Before edge detection, preprocess the image through operations like brightness/contrast adjustment using imadjust() and noise removal using filters such as medfilt2() for median filtering or imgaussfilt() for Gaussian smoothing to enhance edge detection accuracy.

3. Edge Detection Algorithm: Implement edge extraction using MATLAB's built-in edge detection functions. The edge() function supports multiple algorithms including Canny (optimal noise immunity and localization) and Sobel (gradient-based approach) with customizable threshold parameters for sensitivity control.

4. Result Visualization: Display both original and edge-detected images using imshow() function, optionally using subplot() for side-by-side comparison. The code includes proper figure labeling and export capabilities for result documentation.

By following these steps with the provided code, you can implement comprehensive edge detection in MATLAB while gaining deeper understanding of the process through executable source code and comparative result images.