LOCAL TEXTURE DESCRIPTION FRAMEWORK FOR TEXTURE BASED FACE RECOGNITION

• Published in: ICTACT journal on image and video processing Vol. 4; no. 3; pp. 773 - 784
• Main Authors: R, Reena Rose, A, Suruliandi, K, Meena
• Format: Journal Article
• Language: English
• Published: ICT Academy of Tamil Nadu 01.02.2014
• Subjects: Chi-Square Distance Metric; Face Recognition; Local Texture Description Framework; Nearest Neighborhood Classification
• ISSN: 0976-9099; 0976-9102
• DOI: 10.21917/ijivp.2014.0112

Texture descriptors have an important role in recognizing face images. However, almost all the existing local texture descriptors use nearest neighbors to encode a texture pattern around a pixel. But in face images, most of the pixels have similar characteristics with that of its nearest neighbors because the skin covers large area in a face and the skin tone at neighboring regions are same. Therefore this paper presents a general framework called Local Texture Description Framework that uses only eight pixels which are at certain distance apart either circular or elliptical from the referenced pixel. Local texture description can be done using the foundation of any existing local texture descriptors. In this paper, the performance of the proposed framework is verified with three existing local texture descriptors Local Binary Pattern (LBP), Local Texture Pattern (LTP) and Local Tetra Patterns (LTrPs) for the five issues viz. facial expression, partial occlusion, illumination variation, pose variation and general recognition. Five benchmark databases JAFFE, Essex, Indian faces, AT&T and Georgia Tech are used for the experiments. Experimental results demonstrate that even with less number of patterns, the proposed framework could achieve higher recognition accuracy than that of their base models.