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Image Retrieval Based on Improved Supervised LLE Learning Method

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3 Author(s)
Cheng-Dong Zhao ; Dept. of Comput. Sci., Nanjing Univ. of Sci. & Technol., Nanjing, China ; Xu-hui Wang ; Jian-feng Lu

In this paper, identification information is put into the distance measure, using this new distance measure instead of the Euclidean distance to construct k -neighbor, We propose a new improved supervised locally linear embedding method. The IS-LLE method can reduce the vectors dimension with keeping their original topology structure into a lower dimension space, the methods increases the margin of classes in the transformed space. Experiment shows that the proposed IS-LLE method can achieve higher precision rate in CBIR.

Published in:

Pattern Recognition (CCPR), 2010 Chinese Conference on

Date of Conference:

21-23 Oct. 2010