A Novel Approach for Texture Analysis Using Local Binary Pattern for Face Recognition

Texture analysis is an important and useful area of study in machine vision. Texture provides a rich source of information about the natural scene. This paper presents Local Binary pattern (LBP) as an approach for texture analysis particular for face recognition. Face recognition has received quite a lot of attention from researchers in biometrics, pattern recognition, and computer vision communities. The idea behind using the LBP features is that the face images can be seen as composition of micro-patterns which are invariant with respect to monotonic grey scale transformations. Combining these micro-patterns, a global description of the face image is obtained. Efficiency and the simplicity of the proposed method allows for very fast feature extraction giving better accuracy than the other algorithms. The proposed method is tested and evaluated on ORL datasets combined with other university dataset to give a good recognition rate and 89% classification accuracy using LBP only and 98% when global features are combined with LBP. The experimental results show that the method is valid and feasible.