Local Dual-Cross Ternary Pattern for Feature Representation

Peng Zhou, Yucong Peng, Jifeng Shen, Baochang Zhang, Wankou Yang

Abstract: Extracting effective features is a fundamental issue in image representation and recognition. In this paper, we present a new feature representation method for image recognition based on Local Ternary Pattern and Dual-Cross Pattern, named Local Dual-Cross Ternary Pattern (LDCTP). LDCTP is a feature representation inspired by the sole textural structure of human faces. It is efficient and only quadruples the cost of computing Local Binary Pattern. Experiments show that LDCTP outperforms other descriptors.