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T. Srinivasa Rao1, Dr. E. Srinivasa Reddy2
1,2Computer Science & Engineering, Acharya Nagarjuna University, Guntur, India

Abstract: 

Biometric recognition is a process of recognizing an individual with their physiological and behavioral biometric traits. In this paper, a multimodal biometric system is proposed by combining the scores of fingerprint, palmprint and speech traits of a person. This information fusion takes place at the matching score level. Score normalization is a technique to transform the obtained scores into a uniform domain, prior to combining them. The resulting scores are compared to a threshold value for taking a decision of accepting or rejecting the person. The recognition accuracy of fusion methods strongly depends upon the correctness of this threshold value. Hence, we propose crow search optimization (CSO) technique for selecting the optimal threshold value for each of the fusion method employed. The experimental results obtained using finger print, speech and palm print databases show that the application of CSO results in higher recognition rates and lower error rates. To the best of our knowledge, it is the first work that applies CSO to enhance the accuracy of biometric authentication process.

Key Words: multi-modal biometrics, biometric fusion, fingerprint, palmprint, speech, score level fusion.

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Crossref - DOI

 

 dx.doi.org/10.18535/ijetcr 




 



 


 


 


 

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