Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/1202
Title: Coarse iris classification based on box-counting method
Authors: Yu, Li
Wang, Kuanquan
Zhang, David D.
Subjects: Box counting
Fractal dimension
Iris image
Coarse classification
Issue Date: 2005
Publisher: IEEE
Source: 2005 ICIP : 2005 International Conference on Image Processing (ICIP) : September 11-14, 2005, Genova, Italy, v. 3, p. 301-304.
Abstract: This paper proposes a novel algorithm 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 proportions of these categories in our database are 5.50%, 38.54%, 21.79% and 34.17%. The iris images are classified with the double threshold algorithm, which classifies iris images with an accuracy of 94.61%. When we allow for the border effect, the double threshold algorithm is 98.28% accurate.
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Type: Conference Paper
URI: http://hdl.handle.net/10397/1202
ISBN: 0780391349
Appears in Collections:COMP Conference Papers & Presentations

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