4-CLASS CLASSIFICATION OF FINGERPRINT IMAGES USING BIOGEOGRAPHY BASED OPTIMIZATION TECHNIQUES

Fingerprint Analysis is the study of fingerprint features and characteristics associated with the captured image. It is a very popular and highly acceptable field of Biometric Applications. In this work, we have examined a Novel Biogeography based optimized MLANN algorithm for classifying fingerprints as a biometric classifier. For classification the first step is feature extraction based on which the accuracy of classification depends. Here we have collected the features of five different classes of fingerprints using Gabor Filter bank. The fingerprints are collected from NIST database and real-time fingerprints also. The results prove that this method is robust enough to classify the fingerprints with a high accuracy.