Orientation selectivity based structure for texture classification
Date of Issue2014
SPIE 9273, Optoelectronic Imaging and Multimedia Technology III
School of Computer Engineering
Local structure, e.g., local binary pattern (LBP), is widely used in texture classification. However, LBP is too sensitive to disturbance. In this paper, we introduce a novel structure for texture classification. Researches on cognitive neuroscience indicate that the primary visual cortex presents remarkable orientation selectivity for visual information extraction. Inspired by this, we investigate the orientation similarities among neighbor pixels, and propose an orientation selectivity based pattern for local structure description. Experimental results on texture classification demonstrate that the proposed structure descriptor is quite robust to disturbance.
DRNTU::Engineering::Electrical and electronic engineering::Optics, optoelectronics, photonics
© 2014 Society of Photo-optical Instrumentation Engineers. This paper was published in Proceedings of SPIE 9273, Optoelectronic Imaging and Multimedia Technology III and is made available as an electronic reprint (preprint) with permission of Society of Photo-optical Instrumentation Engineers. The paper can be found at the following official DOI: [http://dx.doi.org/10.1117/12.2071438]. One print or electronic copy may be made for personal use only. Systematic or multiple reproduction, distribution to multiple locations via electronic or other means, duplication of any material in this paper for a fee or for commercial purposes, or modification of the content of the paper is prohibited and is subject to penalties under law.