Fingerprint Classification by Filter Bank Approach Using Biogeography Based Optimized Functional Link ANN

In this work, we have examined a Novel Biogeography based optimized FLANN 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 class...

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Bibliographic Details
Published in2018 International Conference on Applied Electromagnetics, Signal Processing and Communication (AESPC) Vol. 1; pp. 1 - 3
Main Authors Mishra, Annapurna, Dehuri, Satchidananda
Format Conference Proceeding
LanguageEnglish
Published IEEE 01.10.2018
Subjects
Biometric
Features
Filter bank
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Summary:In this work, we have examined a Novel Biogeography based optimized FLANN 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-9 database. The results prove that this method is robust enough to classify the fingerprints with a high accuracy.
DOI:10.1109/AESPC44649.2018.9033397