A distinct and compact texture descriptor

作者：Quan Yuhui; Xu Yong^*; Sun Yuping

来源：Image and Vision Computing, 2014, 32(4): 250-259.

DOI：10.1016/j.imavis.2014.02.004

• Texture description
• Local binary pattern
• Fractal dimension
• Multi-fractal analysis
• Texture classification

In this paper, a statistical approach to static texture description is developed, which combines a local pattern coding strategy with a robust global descriptor to achieve highly discriminative power, invariance to photometric transformation and strong robustness against geometric changes. Built upon the local binary patterns that are encoded at multiple scales, a statistical descriptor, called pattern fractal spectrum, characterizes the self-similar behavior of the local pattern distributions by calculating fractal dimension on each type of pattern. Compared with other fractal-based approaches, the proposed descriptor is compact, highly distinctive and computationally efficient. We applied the descriptor to texture classification. Our method has demonstrated excellent performance in comparison with state-of-the-art approaches on four challenging benchmark datasets.

• 出版日期2014-4
• 单位华南理工大学