Face Recognition with Local Binary Patterns
This paper is about providing efficient face recognition i.e. feature extraction and face matching system using local binary patterns (LBP) method. It is a texture based algorithm for face recognition which describes the texture and shape of digital images. The preprocessed or facial image is ﬁrst divided into small blocks from which LBP histograms are formed and then concatenated into a single feature vector. This feature vector plays a vital role in eﬃcient representation of the face and is used to measure similarities by calculating the distance between Images. This paper presents the principles of the method and implementation to perform face recognition. Experiments have been carried out on Yale data set; high recognition rates are obtained, especially compared to other face recognition methods. Also few extensions are investigated and implemented successfully to further improve the performance of the method.