MATLAB Implementation of Fingerprint Recognition with Detailed Code Process

Fingerprint recognition programs represent crucial biometric technology implemented through systematic computational stages. The process initiates with image binarization using thresholding techniques like Otsu's method, converting grayscale fingerprint images into binary format through MATLAB's graythresh() and imbinarize() functions. Subsequently, ridge thinning algorithms such as Zhang-Suen or morphological thinning operations refine the binary image to single-pixel width skeletons, enhancing feature visibility through iterative pixel removal while preserving topological structure. Finally, minutiae extraction identifies key characteristics including ridge endings and bifurcations by analyzing pixel connectivity patterns, typically employing 3x3 scanning windows and cross-number calculations. This integrated pipeline enables precise fingerprint matching through coordinate-based feature comparison, providing reliable identity verification systems with applications in security and access control.