KUALITAS UNJUK KERJA PENDETEKSIAN CITRA IRIS DENGAN WAVELET 2D

Fadlisyah Fadlisyah

doi:10.29103/techsi.v7i1.176

KUALITAS UNJUK KERJA PENDETEKSIAN CITRA IRIS DENGAN WAVELET 2D

Fadlisyah Fadlisyah

Abstract

The performance of an iris recognition system can be undermined by poor quality images and result in high false reject rates (FRR) and failure to enroll (FTE) rates. In this paper, a wavelet-based quality measure for iris images is proposed. The merit of the this approach lies in its ability to deliver good spatial adaptivity and determine local quality measures for different regions of an iris image. Our experiments demonstrate that the proposed quality index can reliably predict the matching performance of an iris recognition system. By incorporating local quality measures in the matching algorithm, we also observe a relative matching performance improvement of about 20% and 10% at the equal error rate (EER), respectively, on the CASIA and WVU iris databases.

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References

Chen, Yi., Dass, Sarat., dan Jain, Anil., 2003. Localized Iris Imaget Quality Using 2-D Wavelets, Journal of Computer Sciences.

Guo, Guodong., 2006. Face, Expression, and Iris Recognition Using

Learned-Based Approaches, Ph.D’s Dissertation, Computer Science University of Wisconsin – Madison, USA

Hsu, Rein-Lein., 2002. Face Detection and Modelling for Recognition, Ph.D’s Dissertation, Depatment of Computer Science & Engineering Michigan State University, USA

Prabhakar, Salil., 2001. Fingerprint Classification and Matching Using a Filterbank, Ph.D’s Dissertation, Depatment of Computer

Science & Engineering Michigan State University, USA

Ross, Arun Abraham., 2003. Information Fusion in Fingerprint

Authentication, Ph.D’s Dissertation, Depatment of Computer

Science & Engineering Michigan State University, USA

DOI: https://doi.org/10.29103/techsi.v7i1.176