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Proceedings Paper

Combination of fractional Brownian random field and lacunarity for iris recognition
Author(s): Kai Liu; Weidong Zhou; Yu Wang
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Paper Abstract

Feature extraction plays a vital role in iris recognition, affecting the performance of iris recognition algorithm strongly. In this paper, we present an individual recognition algorithm using fractal dimension based on fractional Brownian random field and lacunarity in feature extraction. Making use of the fractal feature of iris, such as self-similarity and random patterns, fractal dimension can extract texture information effectively. Lacunarity overcomes the limitation of fractal dimension that fractal sets with different textures may share the same fractal dimension value. The combination of fractal dimension and lacunarity makes the feature extraction more comprehensive and distinguishable. The experimental results show that this recognition algorithm can obtain great performance on CASIA 1.0 iris database

Paper Details

Date Published: 1 October 2011
PDF: 7 pages
Proc. SPIE 8285, International Conference on Graphic and Image Processing (ICGIP 2011), 82856E (1 October 2011); doi: 10.1117/12.913474
Show Author Affiliations
Kai Liu, Shandong Univ. (China)
Weidong Zhou, Shandong Univ. (China)
Yu Wang, Shandong Univ. (China)


Published in SPIE Proceedings Vol. 8285:
International Conference on Graphic and Image Processing (ICGIP 2011)
Yi Xie; Yanjun Zheng, Editor(s)

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