FINGERPRINT RECOGNITION

Abstract

The popular Biometric used to authenticate a person is Fingerprint which is unique and permanent throughout a person’s life. A minutia matching is widely used for fingerprint recognition and can be classified as ridge ending and ridge bifurcation. Automatic minutiae detection is an extremely critical process, especially in low-quality fingerprints where noise and contrast deficiency can originate pixel configurations similar to minutiae or hide real minutiae. The technique describe here, is consists of minutiae extraction and minutiae matching. the minutia extraction algorithm proposed here, is much faster and more reliable and implemented for extracting features from an input fingerprint image. For minutia matching, an alignment-based elastic matching algorithm has been developed. The proposed algorithm results in an efficient, robust and fast representation of fingerprints which accurately retains the fidelity in minutiae (ridge endings and bifurcations).