MATLAB Gabor Feature Computation Toolbox Developed by International Researchers

This article introduces an internationally developed MATLAB toolbox for Gabor feature computation, which provides comprehensive tools for both one-dimensional and two-dimensional Gabor feature extraction. Gabor filters are extensively utilized in computer vision applications due to their exceptional capability to capture local image characteristics. These linear filters can be precisely customized by adjusting key parameters including orientation, frequency, and bandwidth. The toolbox implements efficient algorithms for generating Gabor filter banks through frequency domain transformations and convolution operations, featuring functions like gabor_filter_2d() for spatial domain implementation and gabor_feature_extract() for batch processing. It offers simplified methods for extracting and analyzing Gabor features from images, making it an essential resource in computer vision research and applications. The implementation includes optimized matrix operations for real-time performance and supports both magnitude and phase responses for comprehensive texture analysis.