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2018 | OriginalPaper | Chapter

Iris Recognition Through Score-Level Fusion

Authors : Ritesh Vyas, Tirupathiraju Kanumuri, Gyanendra Sheoran, Pawan Dubey

Published in: Proceedings of 2nd International Conference on Computer Vision & Image Processing

Publisher: Springer Singapore

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Abstract

Although there are many iris recognition approaches available in the literature, there is a trade-off as which approach is giving the most reliable authentication. In this paper, score-level fusion of two different approaches, XOR-SUM Code and BLPOC, is used to achieve better performance than either approach individually. Different fusion strategies are employed to investigate the effect of fusion on genuine acceptance rate (GAR). It is observed that fusion through sum and product schemes provides better result than that through minimum and maximum schemes. For further improvement, sum and product schemes are more explored through weighted sum with different weights. The best GAR and equal error rate (EER) values are 98.83% and 0.95%, respectively. Performance of proposed score-level fusion is also compared with existing approaches.

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previous chapter Effective Denoising with Non-local Means Filter for Reliable Unwrapping of Digital Holographic Interferometric Fringes
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Metadata
Title
Iris Recognition Through Score-Level Fusion
Authors
Ritesh Vyas
Tirupathiraju Kanumuri
Gyanendra Sheoran
Pawan Dubey
Copyright Year
2018
Publisher
Springer Singapore
Book
Proceedings of 2nd International Conference on Computer Vision & Image Processing

Print ISBN: 978-981-10-7894-1

Electronic ISBN: 978-981-10-7895-8

Copyright Year: 2018

DOI
https://doi.org/10.1007/978-981-10-7895-8_3