MATLAB-Based Fingerprint Recognition System

The MATLAB-developed fingerprint recognition program performs multiple processing operations on fingerprint images, including Gabor filtering for ridge pattern enhancement, image binarization using thresholding techniques, and morphological erosion to remove noise artifacts. By implementing machine learning algorithms like Support Vector Machines (SVM), the program accurately determines whether new fingerprint images match existing entries in the database. This system serves as an effective demonstration platform for small-scale fingerprint identification applications. To provide more comprehensive documentation, we can incorporate explanations about fundamental fingerprint recognition principles and application scenarios. Fingerprint recognition represents a biometric identification technology that analyzes and compares ridge patterns and minutiae points in fingerprint images to verify individual identities. This technology finds extensive applications in security domains such as authentication systems, border control, and criminal investigations. The MATLAB-based fingerprint recognition program facilitates convenient research and development in this field through its modular implementation. Key functions include image preprocessing modules for quality enhancement, feature extraction algorithms for minutiae detection, and classification modules using machine learning approaches. The program's flexibility and accuracy make it an ideal tool for optimizing fingerprint recognition system performance and efficiency, with capabilities for parameter adjustment in filtering operations and SVM kernel selection for improved matching precision.