Fingerprint Recognition using MATLAB

This is a MATLAB program focused on fingerprint recognition. The implementation follows a systematic approach to fingerprint identification and verification using image processing and pattern recognition techniques. The program begins by loading fingerprint images and performing preprocessing operations such as noise removal and image enhancement using MATLAB's Image Processing Toolbox functions like imgaussfilt for Gaussian filtering and histeq for histogram equalization. Following preprocessing, the program extracts distinctive fingerprint features including minutiae points (ridge endings and bifurcations) using algorithms like crossing number method for feature detection. These features serve as unique identifiers to distinguish between different fingerprints. The program then employs classification algorithms such as k-nearest neighbors (KNN) or support vector machines (SVM) for fingerprint identification, utilizing MATLAB's Classification Learner app or custom implementation to determine user identity. Finally, the system performance is evaluated using metrics like false acceptance rate (FAR) and false rejection rate (FRR), with suggestions for algorithm optimization and computational efficiency improvements. Through this implementation, users can gain practical understanding of fingerprint recognition technology and its real-world applications in biometric security systems.