An Effective Texture Spectrum Descriptor

Abstract

The center-symmetric local binary pattern (CS-LBP) is an effective extension to local binary pattern (LBP) operator. However, it discards some important texture information because of the ignorance of the center pixel and is hard to choose a threshold for recognizing the flat area. A novel improved CS-LBP operator, named ICS-LBP, is proposed in this paper. The new operator classifies the local pattern based on the relativity of the center pixel and the center-symmetric pixels instead of the gray value differences between the center-symmetric pixels as CS-LBP, which can fully extract the texture information discarded by CS-LBP descriptor. Comparisons are given among the three methods and the experimental results show the performance improvement of the new descriptor.