Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/27250
Title: A novel method for coarse iris classification
Authors: Yu, L
Wang, K
Zhang, D 
Issue Date: 2006
Publisher: Springer
Source: Lecture notes in computer science (including subseries Lecture notes in artificial intelligence and lecture notes in bioinformatics), 2006, v. 3832 LNCS, p. 404-410 How to cite?
Journal: Lecture notes in computer science (including subseries Lecture notes in artificial intelligence and lecture notes in bioinformatics) 
Abstract: This paper proposes a novel method for the automatic coarse classification of iris images using a box-counting method to estimate the fractal dimensions of the iris. First, the iris image is segmented into sixteen blocks, eight belonging to an upper group and eight to a lower group. We then calculate the fractal dimension value of these image blocks and take the mean value of the fractal dimension as the upper and the lower group fractal dimensions. Finally all the iris images are classified into four categories in accordance with the upper and the lower group fractal dimensions. This classification method has been tested and evaluated on 872 iris cases and the accuracy is 94.61 %. When we allow for the border effect, the double threshold algorithm is 98.28% accurate.
Description: International Conference on Biometrics, ICB 2006, Hong Kong, 5-7 January 2006
URI: http://hdl.handle.net/10397/27250
ISBN: 3540311114
9783540311119
ISSN: 0302-9743
EISSN: 1611-3349
Appears in Collections:Conference Paper

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