MATLAB Implementation of Gabor Filter for Edge Detection

The Gabor filter is a powerful tool for detecting edge information in images, particularly beneficial for beginners as it facilitates better understanding and learning of image processing concepts. This filter operates by applying a series of filter kernels to extract features at different orientations and frequencies, effectively capturing edges within images. In MATLAB implementation, key functions like gaborFilterBank create customizable kernels with parameters controlling orientation (theta), wavelength (lambda), and spatial aspect ratio (gamma). The filtering process typically involves convolution using imfilter or conv2 functions, where each kernel responds maximally to edges aligned with its orientation. Through practical implementation, beginners can explore MATLAB's image processing toolbox, analyze frequency-domain characteristics using fft2, and apply this knowledge to solve real-world problems like texture analysis and edge detection in medical or satellite imagery.