Abstract
This paper describes an analysis on the parameters used to construct 2D log-Gabor filters to encode iris patterns. An iris recognition system, composed by segmentation, normalization, encoding and matching is also described. The segmentation module combines the Pulling & Pushing and Active Contour Model and the Circular Hough Transform to find the inner and the outter boundaries of the iris. The experiments were performed using the CASIA v.1 iris database and the results are analyzed using ROC curves. They showed that 2D log-Gabor filters are also an effective alternative to encode the features present on iris patterns.
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Bastos, C.A.C.M., Ren, T.I., Cavalcanti, G.D.C. (2012). Iris Segmentation and Recognition Using 2D Log-Gabor Filters. In: Yin, H., Costa, J.A.F., Barreto, G. (eds) Intelligent Data Engineering and Automated Learning - IDEAL 2012. IDEAL 2012. Lecture Notes in Computer Science, vol 7435. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-32639-4_54
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DOI: https://doi.org/10.1007/978-3-642-32639-4_54
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-32638-7
Online ISBN: 978-3-642-32639-4
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