Because fingerprint patterns are fuzzy in nature and ridge endings are changed easily by scares, 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. Our experimental results have show that the proposed fingerprint recognition system is robust, reliable and rapid.
Relation:
2005年國際系統與信號研討會論文集=Proceedings of 2005 International Conference on System & Signals (ICSS2005)，6頁
