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Title: Coarse iris classification based on box-counting method
Authors: Yu, L
Wang, K
Zhang, DD 
Issue Date: 2005
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.
Keywords: Box counting
Fractal dimension
Iris image
Coarse classification
Publisher: IEEE
ISBN: 0-7803-9134-9
Rights: © 2005 IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE.
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