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Title: Texture discrimination by local morphological multifractal signatures
Authors: Xia, Y
Zhao, R
Zhang, Y
Feng, DD
Sun, J
Issue Date: 2006
Source: TENCON 2006 : 2006 IEEE Region 10 Conference : Hong Kong, China, 14-17 November, 2006, p. [1-4] (CD)
Abstract: Both the fractal dimension (FD) and the multifractal dimensions (MFD) have been widely used to describe natural textures in image processing community. However, due to the essential difference between the fractal reality of digital images and the mathematical fractal model, most FD/MFD estimation algorithms intrinsically produce less accurate results. In this paper, the idea of fractal signature is adopted and extended to the morphological multifractal estimation. As a result, a novel texture descriptor, namely the local morphological multifractal signatures (LMMS), is proposed to characterize the local scaling property of textured images. The LMMS depict the behavior of the morphological MFD over a wide range of spatial scales. The proposed LMMS feature, together with the fractal signature and the morphological MFD, has been applied to the discrimination of Brodatz textures. The comparison results demonstrate that our LMMS feature can differentiate natural textures more effectively.
Keywords: Fractals
Image texture
Mathematical morphology
Publisher: IEEE
ISBN: 1-4244-0549-1
DOI: 10.1109/TENCON.2006.344115
Rights: © 2006 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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