MATLAB Algorithm for Gradient Edge Detection in Color Images

This MATLAB program implements a gradient-based edge detection algorithm for color images. The algorithm extracts gradient edges where pixel intensity changes occur in an image. By detecting these edges, we can obtain object contours for applications like image segmentation and object detection. The implementation includes fundamental image processing steps: - Grayscale conversion using rgb2gray() function to reduce computational complexity - Smoothing filtration with Gaussian or median filters to reduce noise - Gradient computation using Sobel, Prewitt, or Roberts operators through imgradient() function - Edge thresholding and non-maximum suppression for clean edge maps Key MATLAB functions utilized: 1. imread() for image loading 2. rgb2gray() for color-to-grayscale conversion 3. fspecial() for filter kernel creation 4. imfilter() for convolution operations 5. imgradient() for gradient magnitude and direction calculation This program demonstrates practical MATLAB techniques for color image processing while explaining the mathematical principles behind gradient edge detection, including gradient vector calculation and edge magnitude thresholds.