Fingerprint Classification by Filter Bank Approach Using Evolutionary ANN
This paper presents an evolutionary artificial neural network for classification of fingerprints in the area of biometric recognition. An efficient way for feature extraction from the fingerprints using a Gabor filter bank has been studied very rigorously and extracted potentially useful features. Here five classes of fingerprints have been taken into consideration. We have conducted experimental study to prove the effectiveness of the method on NIST-9 database. It is evident from the results that the method is effective in classifying the fingerprints with a varying degree of accuracy vis-à-vis to the different parameters setting.
KeywordsClassification Gabor filter EANN Feature extraction Evolutionary
The first author would like to thank the technical support of Department of Information and Communication Technology, Fakir Mohan University, Vyasa Vihar, Balasore.
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