Abstract
To investigate the robustness of face recognition algorithms under the complicated variations of illumination, facial expression and posture, the advantages and disadvantages of seven typical algorithms on extracting global and local features are studied through the experiments respectively on the Olivetti Research Laboratory database and the other three databases (the three subsets of illumination, expression and posture that are constructed by selecting images from several existing face databases). By taking the above experimental results into consideration, two schemes of face recognition which are based on the decision fusion of the two-dimensional linear discriminant analysis (2DLDA) and local binary pattern (LBP) are proposed in this paper to heighten the recognition rates. In addition, partitioning a face non-uniformly for its LBP histograms is conducted to improve the performance. Our experimental results have shown the complementarities of the two kinds of features, the 2DLDA and LBP, and have verified the effectiveness of the proposed fusion algorithms.
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Qicong Wang received the PhD degree from Zhejiang University, China in 2007. He is currently an associate professor at the Department of Computer Science, Xiamen University, China. His research interests include pattern recognition, machine learning and computer vision.
Binbin Wang received the BE degree and the ME degree in 2010 and 2013, respectively, both from Xiamen University, China. She is currently a software engineer at the center of software development of Industrial and Commercial Bank of China, Guangdong.
Xinjie Hao received the BE degree and the ME degree in 2010 and 2013, respectively, both from Xiamen University, China. He is currently a postgraduate student majoring computer science at Worcester Polytechnic Institute, USA. His research interests include machine learning and image processing.
Lisheng Chen received the BE degree and the ME degree in 2010 and 2013, respectively, both from Xiamen University, China. He is currently a technical manager at the department of Internet products of Hebao Financial Information Consultant Co. Ltd., Shenzhen, China.
Jingmin Cui received the BE degree and the ME degree in 2010 and 2013, respectively, both from Xiamen University, China. She is currently a system analyst (SA) at the Research and Development Center (Shenzhen), the Bank of Communications, China.
Rongrong Ji received the PhD degree from Harbin Institute of Technology, China. He had been a Postdoctoral Research Fellow in Columbia University, USA. Currently he is a Minjiang Chair Professor of Xiamen University, China. His research interests include machine learning and computer vision.
Yunqi Lei received the BE degree from the University of Science and Technology of China, China in 1982, and the PhD degree from the National University of Defense Technology, China in 1988. Currently, he is a professor at the Department of Computer Science, Xiamen University, China. His research interests include machine learning and computer vision.
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Wang, Q., Wang, B., Hao, X. et al. Face recognition by decision fusion of two-dimensional linear discriminant analysis and local binary pattern. Front. Comput. Sci. 10, 1118–1129 (2016). https://doi.org/10.1007/s11704-016-5024-6
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DOI: https://doi.org/10.1007/s11704-016-5024-6