Fusing Fingerprint and Iris Multimodal Biometrics using Soft Computing Techniques 

Abstract

This paper presents the application of soft computing techniques in multimodal biometrics recognition. The paper investigates the comparative performance of three different approaches: nonoptimized neural network trained with unimodal biometrics, non-optimized neural network trained with multimodal fingerprint and iris biometrics and optimized neural network trained with fingerprint and iris biometrics. The experimental results suggest that neural network optimized with genetic algorithm shows better recognition rate as compared to the other two approaches. The performance evaluation of each method is reported in terms of mean square error, percentage error, and accuracy.

Authors and Affiliations

Tanvi Dhingra , Manvjeet Kaur

Keywords

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  • EP ID EP153413
  • DOI -
  • Views 112
  • Downloads 0

How To Cite

Tanvi Dhingra, Manvjeet Kaur (2015). Fusing Fingerprint and Iris Multimodal Biometrics using Soft Computing Techniques . International Journal of Computer Science & Engineering Technology, 6(6), 392-398. https://europub.co.uk./articles/-A-153413