Wavelet-based Feature Extraction Algorithm for an Iris Recognition System

Ayra Panganiban, Noel Linsangan and Felicito Caluyo
Volume: 7, No: 3, Page: 425 ~ 434, Year: 2011
10.3745/JIPS.2011.7.3.425
Keywords: Biometrics, Degrees of Freedom, Iris Recognition, Wavelet
Full Text:

Abstract
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.

Article Statistics
Multiple requests among the same broswer session are counted as one view (or download).
If you mouse over a chart, a box will show the data point's value.


Cite this article
IEEE Style
Ayra Panganiban, Noel Linsangan and Felicito Caluyo, "Wavelet-based Feature Extraction Algorithm for an Iris Recognition System," Journal of Information Processing Systems, vol. 7, no. 3, pp. 425~434, 2011. DOI: 10.3745/JIPS.2011.7.3.425.

ACM Style
Ayra Panganiban, Noel Linsangan and Felicito Caluyo, "Wavelet-based Feature Extraction Algorithm for an Iris Recognition System," Journal of Information Processing Systems, 7, 3, (2011), 425~434. DOI: 10.3745/JIPS.2011.7.3.425.