Texture analysis by fractal descriptors over the wavelet domain using a best basis decomposition

J.B. Florindo and O.M. Bruno

Physica A: Statistical Mechanics and its Applications, 2016, vol. 444, issue C, 415-427

Abstract: This work proposes the development and study of a novel set of fractal descriptors for texture analysis. These descriptors are obtained by exploring the fractal-like relation among the coefficients and magnitudes of a particular type of wavelet decomposition, to know, the best basis selection. The proposed method is tested in the classification of three sets of textures from the literature: Brodatz, Vistex and USPTex. The method is also applied to a challenging real-world problem, which is the identification of species of plants from the Brazilian flora. The results are compared with other classical and state-of-the-art texture descriptors and demonstrate the efficiency of the proposed technique in this task.

Keywords: Pattern recognition; Fractal descriptors; Wavelet transform; Best basis selection; Texture analysis (search for similar items in EconPapers)
Date: 2016
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Persistent link: https://EconPapers.repec.org/RePEc:eee:phsmap:v:444:y:2016:i:c:p:415-427

DOI: 10.1016/j.physa.2015.10.031

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