Explore MATLAB source code curated for "指纹识别" with clean implementations, documentation, and examples.
This program provides MATLAB code for fingerprint recognition, featuring a comprehensive pipeline including fingerprint enhancement, orientation and ridge estimation, binary masking, and feature extraction. The classification module analyzes input images to determine matching identities, implementing pattern comparison algorithms for final verification.
Fingerprint Recognition MATLAB Implementation with Complete Source Code and Algorithm Explanations
Implementation of post-processing fingerprint feature extraction and matching algorithms for fingerprint recognition, featuring custom .m files for enhanced performance when integrated with preprocessing stages - includes key functions for minutiae detection, similarity scoring, and template comparison
This project provides a comprehensive MATLAB solution for fingerprint recognition, including detailed technical documentation and full source code. The implementation covers image preprocessing, feature extraction, and matching algorithms for biometric authentication systems.
Install the fingerprint recognition MATLAB source code in your MATLAB working directory, then execute the main program fprec.m to initiate fingerprint identification. The system employs sophisticated image processing algorithms and feature extraction techniques for accurate biometric authentication.
Fingerprint image preprocessing procedures in fingerprint recognition, including normalization, binarization, image segmentation, image enhancement, and image visualization with algorithmic implementations
Several fingerprint matching techniques exist, with the most widely used being: Correlation-based matching, which computes similarity across different pixel paths and rotations but suffers from high computational complexity. Feature point-based matching, the most popular technique, identifies and maps minutiae points for comparison, yet faces challenges with low-quality fingerprints. Pattern-based (image-based) matching compares fingerprint patterns (arches, whorls, loops) between templates and candidate images but requires precise alignment. Implementation considerations include algorithmic efficiency, preprocessing requirements, and reliability under varying image quality conditions.
A fingerprint recognition algorithm implementing Gabor filtering technique with enhanced precision and detailed code implementation insights.
A comprehensive MATLAB fingerprint recognition program featuring advanced image processing algorithms and pattern matching techniques - highly recommended for biometric applications!
This code implements fingerprint recognition through preprocessing, feature extraction, and classification algorithms using image processing and machine learning techniques.