Feature Level Fusion of Iris and Fingerprint Biometrics for personal identification using Artificial Neural Network
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Abstract
This research presents the multi –modal biometric system for iris and fingerprint This paper presents the Feature level fusion using wavelet for combining two unimodal biometric system. Gabor transform is used for feature extraction and wavelet transformation for fusion of iris and fingerprint. The system applied artificial neural network technique for recognizing whether the user is genuine (accepted) or impostor (rejected). The proposed system is for multimodal database comprising of 20 samples. The performance of the system is tested on a database prepared to find accuracy, false acceptance rate and false rejection rate.
DOI: 10.17762/ijritcc2321-8169.150774
DOI: 10.17762/ijritcc2321-8169.150774
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How to Cite
, E. P. K. S. D. R. C. G. E. I. S. (2015). Feature Level Fusion of Iris and Fingerprint Biometrics for personal identification using Artificial Neural Network. International Journal on Recent and Innovation Trends in Computing and Communication, 3(7), 4719–4723. https://doi.org/10.17762/ijritcc.v3i7.4722
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Articles