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| Image Classification Using Modified ISOMAP Method |
| WEI Xian,LI Yuanxiang,ZHAO Haitao,TUO Hongya,XU Peng |
| (School of Aeronautics & Astronautics, Shanghai Jiaotong University, Shanghai 200240, China) |
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Abstract The classical ISOMAP（isometric feature mapping，ISOMAP） method developed on reconstruction principle may not be optimal from the classification viewpoint. Besides，it is prone to suffer from the noise and the range of the neighborhood. In order to resolve these problems, a novel method called KIMDISOMAP for dimensionality reduction was presented. Firstly, a modified image euclidean distance is proposed and used to find the suitable neighborhood. Then, direct linear discriminant analysis (Direct LDA) is used to replace multidimensional scaling (MDS). Compared with ISOMAP, the experiments on face recognition show that KIMDISOMAP enhances the ability of classification and extends the range of the neighborhood. In addition, the KIMDISOMAP obtains a better performance than other algorithms for images classification with small noise and geometrical deformation.
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Received: 04 September 2009
Published: 28 July 2010
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