Performance Improvement of Authentication of Fingerprints Using Enhancement and Matching Algorithms
Fingerprint is one of the most extensively used biometric systems for authentication in areas where security is of high importance. This is due to their permanence, accuracy and reliability. However, extracting features out of degraded fingerprints is the most challenging in order to obtain high fingerprint matching performance. This paper intends to enhance the clarity of fingerprint minutiae, removing false minutiae and improve the matching performance using a Gabor filtering technique and artificial neural network. The experiments showed improved results as compared with results of fingerprints that were not enhanced.