A New Texture Descriptor Using Multifractal Analysis in Multi-orientation Wavelet Pyramid

Based on multifractal analysis in wavelet pyramids of texture images, a new texture descriptor is proposed in this paper that implicitly combines information from both spatial and frequency domains. Beyond the traditional wavelet transform, a multi-oriented wavelet leader pyramid is used in our approach that robustly encodes the multi-scale information of texture edgels. Moreover, the resulting texture model shows empirically a strong power law relationship for nature textures, which can be characterized well by multifractal analysis. Combined with a statistics on affine invariant local patches, our proposed texture descriptor is robust to scale and rotation changes, more general geometrical transforms and illumination variations. In addition, the proposed texture descriptor is computationally efficient since it does not require many expensive processing steps, e.g., texton generation and cross-bin comparisons, which are often used by existing methods. As an application, the propose...

• Type: Conference
• Year: 2010
• Where: CVPR
• Authors: Yong Xu, Xiong Yang, Haibin Ling, Hui Ji
• Keywords: Computer Vision, CVPR 2010, Multifractal Analysis, Texture Descriptor, Texture Images