Fingerprint Verification System Using Artificial Neural Network

A fingerprint is typically classified based on only the first type of features and uniquely identified based on the second type of features. The fingerprint verification system is the most perfect process to identify a person. The digital values of these features (Minutiae, ridge ending and bifurcation) are applied to the input of the neural network for training purpose using back propagation algorithm of Artificial Neural Network. During the training period, the values of the nodes are updated and stored in a relational knowledge base. For fingerprint recognition, the verification part of the system identifies the Fingerprint of a person with the help of the previous experiential values, which was stored in the relational knowledge base system. Finally, it is concluded that the performance of recognition of fingerprint using the minutiae features-based fingerprint verification system is better.