Open AccessWavelet-based Feature Extraction Algorithm for an Iris Recognition System
Author(s) -
Ayra G. Panganiban,
Noel B. Linsangan,
Felicito S. Caluyo
Publication year - 2011
Publication title -
journal of information processing systems
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.288
H-Index - 23
eISSN - 2092-805X
pISSN - 1976-913X
DOI - 10.3745/jips.2011.7.3.425
Subject(s) - iris recognition , computer science , normalization (sociology) , artificial intelligence , pattern recognition (psychology) , wavelet , haar wavelet , word error rate , feature (linguistics) , biorthogonal wavelet , iris (biosensor) , feature extraction , biorthogonal system , wavelet transform , algorithm , biometrics , computer vision , discrete wavelet transform , linguistics , philosophy , sociology , anthropology
The success of iris recognition depends mainly on two factors: image acquisition and an iris recognition algorithm. In this study, we present a system that considers both factors and focuses on the latter. The proposed algorithm aims to find out the most efficient wavelet family and its coefficients for encoding the iris template of the experiment samples. The algorithm implemented in software performs segmentation, normalization, feature encoding, data storage, and matching. By using the Haar and Biorthogonal wavelet families at various levels feature encoding is performed by decomposing the normalized iris image. The vertical coefficient is encoded into the iris template and is stored in the database. The performance of the system is evaluated by using the number of degrees of freedom, False Reject Rate (FRR), False Accept Rate (FAR), and Equal Error Rate (EER) and the metrics show that the proposed algorithm can be employed for an iris recognition system.
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