Humanoid Fingerprint Recognition based on Fuzzy Neural Network

Nowadays the computer speed is much faster than before, however well-trained humans are still the best pattern recognizer. In this paper we propose a fingerprint recognition method which is based on humanoid algorithms. Because fingerprint patterns are fuzzy in nature and ridge endings are changed easily by scars, we try to only use ridge bifurcation as fingerprints minutiae and also design a “fuzzy feature image” encoder by using cone membership function to represent the structure of ridge bifurcation features extracted from fingerprint. Then, we integrate the fuzzy encoder with back-propagation neural network (BPNN) as a recognizer which has variable fault tolerances for fingerprint recognition. Experimental results show that the humanoid fingerprint recognition system is robust, reliable and rapid. Key-Words: Humanoid fingerprint identification; Fuzzy system; Neural networks