AN AUTHENTICATION SYSTEM USING FINGERPRINT MINUTIAE EXTRACTION AND NEURAL NETWORK

Fingerprints have been the mostly used biometrics for human authentication, based on the minutiae or bifurcation. In this paper, the triangle shapes are used to extract features based on minutiae point. The features have been used as a set of descriptors for the fingerprint data. This set of descriptors is fed to the backpropagation neural network for the purpose of fingerprint recognition. It is found that the process of preprocessing and the method of constructing geometric shapes has great effects on producing good results in the recognition rate.