Viewpoint Invariant Texture Description Using Fractal Analysis

作者:Yong Xu, Hui Ji, Cornelia Fermüller

摘要

Image texture provides a rich visual description of the surfaces in the scene. Many texture signatures based on various statistical descriptions and various local measurements have been developed. Existing signatures, in general, are not invariant to 3D geometric transformations, which is a serious limitation for many applications. In this paper we introduce a new texture signature, called the multifractal spectrum (MFS). The MFS is invariant under the bi-Lipschitz map, which includes view-point changes and non-rigid deformations of the texture surface, as well as local affine illumination changes. It provides an efficient framework combining global spatial invariance and local robust measurements. Intuitively, the MFS could be viewed as a “better histogram” with greater robustness to various environmental changes and the advantage of capturing some geometrical distribution information encoded in the texture. Experiments demonstrate that the MFS codes the essential structure of textures with very low dimension, and thus represents an useful tool for texture classification.

论文关键词:Fractal dimension, Multi-fractal spectrum, Viewpoint invariance, Texture description, Texture classification

论文评审过程:

论文官网地址:https://doi.org/10.1007/s11263-009-0220-6