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| 2-Dimensional Kernel Discriminant Analysis Based on Image Sampling and Regrouping |
| Cheng Zheng-dong①②③; Fan Xiang①②④; Zhang Yu-jin③ |
①State Key Laboratory of Pulsed Power Laser Technology (Electronic Engineering Institute), Hefei 230037, China; ②Electronic Engineering Institute, Hefei 230037, China; ③Electronic Engineering Department of Tsinghua University, Beijing 100084, China;
④Science and Technology University of China, Hefei 230027, China |
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Abstract 2-Dimensional Kernel Discriminant Analysis (2DKDA) can not be performed since its scatter metric matrices are too large. This paper combines the sampling and regrouping images with 2DKDA and gives three kinds of Sampling and Regrouping 2-Dimensional Kernel Discriminant Analysis (SR2DKDA). These algorithms not only overcome the drawback of 2DKDA but also have superior recognition accuracy to 2-Dimensional Linear Discriminant Analysis (2DLDA). The experiments on ORL database and UMIST database verify the efficiency of the SR2DKDA.
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Received: 08 December 2008
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2009, Vol. 31 
