Iris recognition by local extremum points of multiscale Taylor expansion

被引:16
作者
Bastys, A. [1 ]
Kranauskas, J. [1 ]
Masiulis, R. [1 ]
机构
[1] Vilnius State Univ, Vilnius, Lithuania
关键词
Iris; Segmentation; Similarity; Warping; Recognition; Verification; Local features; ZERO-CROSSINGS; INFORMATION;
D O I
10.1016/j.patcog.2008.12.004
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
Rich texture of iris image allows to perform iris-based person authentication with very high confidence. We propose to use the most significant local extrema of the first two Taylor expansion coefficients as descriptors of the iris texture. The proposed features can be efficiently compared and even can correct moderate inaccuracies in iris segmentation during the matching stage. A brief introduction of our iris segmentation algorithm is followed by the analysis of the proposed features and the similarity function. We provide experimental results of verification quality for three commonly used iris data sets. An analysis of strong and weak aspects of the proposed approach is done. (C) 2008 Elsevier Ltd. All rights reserved.
引用
收藏
页码:1869 / 1877
页数:9
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