WSEAS Transactions on Computers
Print ISSN: 1109-2750, E-ISSN: 2224-2880
Volume 14, 2015
A New Local Binary Probabilistic Pattern (LBPP) and Subspace Methods for Face Recognition
Authors: , ,
Abstract: In this paper, we present a new model of extraction of local characteristics, named Local Binary Probabilistic Pattern (LBPP), and based on the Local Binary Pattern (LBP). This model relates to a very important result of probability theory; it is the large great numbers. In this respect, the distribution of the gray levels on the areas (homogeneous texture) on a face image follows a law of probability, which is the sum of several normal laws. This vision allows evaluating the current pixel while basing on the concept of confidence interval, which permits to overcome some LBP shortcomings, especially the information losses associated to LBP deterministic nature. We have combined the proposed model with the most known algorithms of the dimensionality reduction of data analysis in the face recognition field. In order to evaluate our approach, various experiments are carried out on data bases ORL and YALE. In this context, we made a comparison between the performances of systems LBP+ACP, LBP+LDA, LBP+2DPCA, LBP+2DLDA, LBPP+ACP, LBPP+LDA, LBPP+2DPCA and LBPP+2DLDA. The obtained results show the effectiveness of our systems, in particular for systems LBPP+2DPCA and LBPP+2DLDA. The experimental exactitude observed is of 96.5%.
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Pages: 588-597
WSEAS Transactions on Computers, ISSN / E-ISSN: 1109-2750 / 2224-2880, Volume 14, 2015, Art. #58