MATLAB Implementation of Edge Feature Extraction

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Resource Overview

Edge feature extraction implementation supporting four algorithms: Prewitt, Roberts, Log, and Canny with code-level explanations for each operator's implementation approach.

Detailed Documentation

Edge feature extraction is a fundamental technique in computer vision that identifies significant boundaries within images. This implementation provides four distinct edge detection algorithms: Prewitt, Roberts, Laplacian of Gaussian (Log), and Canny. The Prewitt operator uses horizontal and vertical gradient approximations through convolution kernels to detect edges. Roberts cross operator employs 2x2 kernels for diagonal gradient calculations. Log algorithm applies Gaussian smoothing followed by Laplacian operator for zero-crossing detection. Canny edge detection implements a multi-stage process including Gaussian filtering, gradient calculation, non-maximum suppression, and double thresholding. These algorithms enable effective extraction of edge information from images, facilitating better understanding of image structure and content through MATLAB's image processing toolbox functions like edge() with appropriate method parameters.

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