MATLAB Implementation of Fingerprint Recognition Algorithm Using Gabor Filter

This text describes a fingerprint recognition algorithm program implemented in MATLAB, which employs Gabor filters as the core processing technique. The algorithm represents a widely-used fingerprint recognition approach that performs accurate fingerprint identification through image filtering and feature extraction operations. In the implementation, Gabor filters function as frequency-domain-based filters that conduct multi-scale and multi-orientation feature extraction on fingerprint images, effectively capturing detailed texture patterns and ridge characteristics. The MATLAB code typically involves several key steps: preprocessing the input fingerprint image, configuring Gabor filter parameters (including wavelength, orientation, and bandwidth), applying the filter bank to extract ridge features, and performing post-processing for matching decisions. Through this algorithm implementation, we achieve more accurate and reliable fingerprint recognition, providing crucial technical support for security verification and personal identity confirmation applications. The code structure may include functions for Gabor filter generation, convolution operations with fingerprint images, and feature vector computation for comparison purposes.