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Proceedings Paper

Texture segmentation with discrete fractional Brownian wavelet random field
Author(s): Huiguo Luo; Yaoting Zhu; Guang-Xi Zhu; Faguang Wan
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Paper Abstract

Fractal-based image processing has been applied in many areas in recent years. Many researchers have discussed its application in feature detection, texture segmentation, obtaining 3D information etc. Fractinal Brownian Random field (FBR) is the basic fractal image model, but it contains some problems. First, FBR is isotropic, but nature images generally are anisotropic. Second, FBR is nonstable, it is not easy for processing. For solving these problems, in this paper we present a new fractal image model--Discrete Fractional Brownian Wavelet Random Field (DFBWR). It is the wavelet transform of FBR. After giving the definition of DFBWR, we discussed some important properties. We can estimate the parameter H with DFBWR. According to these H values, we can segment the textures. At last, we give a texture segmentation result of an experiment.

Paper Details

Date Published: 29 October 1993
PDF: 4 pages
Proc. SPIE 2032, Neural and Stochastic Methods in Image and Signal Processing II, (29 October 1993); doi: 10.1117/12.162037
Show Author Affiliations
Huiguo Luo, Huazhong Univ. of Science and Technology (United States)
Yaoting Zhu, Huazhong Univ. of Science and Technology (China)
Guang-Xi Zhu, Huazhong Univ. of Science and Technology (China)
Faguang Wan, Huazhong Univ. of Science and Technology (China)


Published in SPIE Proceedings Vol. 2032:
Neural and Stochastic Methods in Image and Signal Processing II
Su-Shing Chen, Editor(s)

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