Classic Gabor Filter Source Code with MATLAB Implementation

This is a classic Gabor filter source code implementation using MATLAB. The Gabor filter represents a fundamental image processing algorithm widely employed for image feature extraction and analysis. By utilizing Gabor filters, we can effectively capture texture patterns and edge information from images, making them valuable for applications such as image recognition, object detection, and facial recognition systems. The MATLAB implementation provides a practical framework for processing and analyzing images through Gabor filtering. The code typically involves creating Gabor kernels with specific parameters including orientation, wavelength, and spatial frequency bandwidth. Key functions may include gaborFilterBank creation for multiple orientations, convolution operations with input images, and feature vector extraction from filter responses. Implementation aspects cover: - Generating complex Gabor wavelets using sinusoidal carriers modulated by Gaussian envelopes - Configurable parameters for scale and orientation variations - Efficient convolution techniques for 2D image filtering - Real and imaginary component processing for comprehensive texture analysis This implementation enables researchers and developers to better understand and leverage image information through systematic filter bank applications. If you're interested in image processing and algorithm implementation, I can provide additional technical details about Gabor filter parameter optimization, performance considerations, and practical code examples. Please feel free to share your specific requirements and questions.