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《Journal of China University of Metrology》 2013-01
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Face recognition method based on modular sparse representation and 2DPCA

Tan Yuanpeng,Cai Miaomiao,Cao Feilong(College of Sciences,China Jiliang University,Hangzhou 310018,China)  
A new face recognition method based on modular sparse representation and two-dimensional principal component analysis(2DPCA) was proposed.The segmentation of pixel and 2DPCA were combined to take full consideration of the correlation between the adjacent pixels.The experimental results demonstrated that the proposed method is feasible and effective.Further research showed that the new method reduces the false acceptance rate significantly on the images with position migration and black blocks,compared with traditional algorithms.
【Fund】: 国家自然科学基金资助项目(No.61272023);; 浙江省研究生创新科研项目(No.YK2011070)
【CateGory Index】: TP391.41
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