Texture segmentation with discrete fractional Brownian wavelet random field

Huiguo Luo; Yaoting Zhu; Guang-Xi Zhu; Faguang Wan

doi:10.1117/12.162037

29 October 1993 Texture segmentation with discrete fractional Brownian wavelet random field

Huiguo Luo, Yaoting Zhu, Guang-Xi Zhu, Faguang Wan

Proceedings Volume 2032, Neural and Stochastic Methods in Image and Signal Processing II; (1993) https://doi.org/10.1117/12.162037
Event: SPIE's 1993 International Symposium on Optics, Imaging, and Instrumentation, 1993, San Diego, CA, United States

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.

Citation Download Citation

Huiguo Luo, Yaoting Zhu, Guang-Xi Zhu, and Faguang Wan "Texture segmentation with discrete fractional Brownian wavelet random field", Proc. SPIE 2032, Neural and Stochastic Methods in Image and Signal Processing II, (29 October 1993); https://doi.org/10.1117/12.162037

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