Combination of fractional Brownian random field and lacunarity for iris recognition

Kai Liu; Weidong Zhou; Yu Wang

doi:10.1117/12.913474

1 October 2011 Combination of fractional Brownian random field and lacunarity for iris recognition

Kai Liu, Weidong Zhou, Yu Wang

Proceedings Volume 8285, International Conference on Graphic and Image Processing (ICGIP 2011); 82856E (2011) https://doi.org/10.1117/12.913474
Event: 2011 International Conference on Graphic and Image Processing, 2011, Cairo, Egypt

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

Citation Download Citation

Kai Liu, Weidong Zhou, and Yu Wang "Combination of fractional Brownian random field and lacunarity for iris recognition", Proc. SPIE 8285, International Conference on Graphic and Image Processing (ICGIP 2011), 82856E (1 October 2011); https://doi.org/10.1117/12.913474

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KEYWORDS

Fractal analysis

Iris recognition

Feature extraction

Detection and tracking algorithms

Databases

Image segmentation

Biometrics

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