Fast k-nearest neighbor search algorithm based on pyramid structure of wavelet transform and its application to texture classification |
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| Authors: | Yu-Long Qiao Zhe-Ming Lu Jeng-Shyang Pan Sheng-He Sun |
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| Affiliation: | 1. College of Information and Communication Engineering, Harbin Engineering University, Harbin, China;2. Department of Automatic Test and Control, Harbin Institute of Technology, Harbin, China;3. School of Aeronautics and Astronautics, Zhejiang University, Hangzhou, China;4. Department of Electronic Engineering, National Kaohsiung University of Applied Sciences, Taiwan |
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| Abstract: | Traditional fast k-nearest neighbor search algorithms based on pyramid structures need either many extra memories or long search time. This paper proposes a fast k-nearest neighbor search algorithm based on the wavelet transform, which exploits the important information hiding in the transform coefficients to reduce the computational complexity. The study indicates that the Haar wavelet transform brings two kinds of important pyramids. Two elimination criteria derived from the transform coefficients are used to reject those impossible candidates. Experimental results on texture classification verify the effectiveness of the proposed algorithm. |
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