Comparative Analysis of Texture Models for Face Recognition

Face Recognition is one of the major issues in biometric technology. It identifies and verifies a person by using physical characteristics of the face images. In this paper, three texture models are compared. The models include Local Binary Pattern (LBP), Local Ternary Pattern (LTP) and Local Line Binary Pattern (LLBP). LBP is defined as a gray scale invariant texture measure, derived from a general definition of texture in a local neighborhood. Facial features are extracted and compared using k nearest neighbor algorithm. Chi-square distance measure is used for comparison. Experiments were carried out on Yale, Yale B and ORL databases. The results show LBP performs better than the other two models.