Iris recognition based on multialgorithmic fusion

Authors:
Fenghua Wang;Jiuqiang Han;Xianghua Yao
Affiliations:
School of Electronics and Information Engineering, Xi'an Jiaotong University, Xi'an, China;School of Electronics and Information Engineering, Xi'an Jiaotong University, Xi'an, China;School of Electronics and Information Engineering, Xi'an Jiaotong University, Xi'an, China
Venue:
WSEAS Transactions on Information Science and Applications
Year:
2007

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Abstract

Fusion of multiple algorithms for biometric verification performance improvement has received considerable attention. This paper proposes an iris recognition method based on multialgorithmic fusion. The proposed method combines the phase information based algorithm and zero-crossing representation based algorithm at the matching score level. The fusion rule based on support vector machine (SVM) is applied to generate a fused score which is used to make the fial decision. The experimental results on CASIA and UBIRIS iris image databases show that the proposed multialgorithmic fusion method can bring obvious performance improvement compared with any single algorithm, and the results also demonstrate that the fusion rule based on SVM can achieve better performance than conventional 1 fusion rules.