Accurate feature extraction for multimodal biometrics combining iris and palmprint

被引:0
作者
Ritesh Vyas
Tirupathiraju Kanumuri
Gyanendra Sheoran
Pawan Dubey
机构
[1] Lancaster University,
[2] National Institute of Technology Delhi,undefined
来源
Journal of Ambient Intelligence and Humanized Computing | 2022年 / 13卷
关键词
Multimodal biometrics; Iris recognition; Palmprint recognition; Bit-transition code;
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中图分类号
学科分类号
摘要
Multimodal biometric systems provide a way to combat with the limitations of a unimodal biometric system which include less accuracy and user acceptability. In this context, a coding based approach called bit-transition code, is proposed for addressing the less-explored problem of designing a biometric-based authentication system by combining the iris and palmprint modalities. The approach is based on the encoding of binary transitions of symmetric and asymmetric parts of the Gabor filtered images at all pixel locations. Score-level fusion is employed to integrate the individual iris and palmprint performances. Experiments are carried out with three benchmark iris/palmprint databases, namely IITD iris and palmprint databases and PolyU palmprint database. The performance is measured in terms of receiver operator characteristics (ROC) curves and other metrics, like equal error rate and area under ROC curves. A comprehensive comparison, with several state-of-the-art approaches, is presented in order to validate the usefulness of the proposed approach.
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页码:5581 / 5589
页数:8
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