Abstract

Texture feature plays a predominant role in recognizing face images. However different persons can have similar texture features that may degrade the system performance. Hence in this paper, the problem of face similarity is addressed by proposing a solution which combines textural and geometrical features. An algorithm is proposed to combine these two features. Five texture descriptors and few geometrical features are considered to validate the proposed system. Performance evaluations of these features are carried out independently and jointly for three different issues such as expression variation, illumination variation and partial occlusion with objects. It is observed that the combination of textural and geometrical features enhance the accuracy of face recognition. Experimental results on Japanese Female Facial Expression (JAFFE) and ESSEX databases indicate that the texture descriptor Local Binary Pattern achieves better recognition accuracy for all the issues considered.

Authors

A. Suruliandi¹, R. Reena Rose², K. Meena³
Manonmaniam Sundaranar University, India¹, St. Xavier’s Catholic College of Engineering, India², Sardar Raja College of Engineering, India^/3

Keywords

Face Recognition, Texture Features, Geometric Features, Nearest Neighborhood Classification, Chi-Square Distance Metric