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A point symmetry-based clonal selection clustering algorithm and its application in image compression

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Abstract

To cluster data set with the character of symmetry, a point symmetry-based clonal selection clustering algorithm (PSCSCA) is proposed in this paper. Firstly, an immune vaccine operator is introduced to the classical clonal selection algorithm, which can gain a priori knowledge of pending problems so as to accelerate the convergent speed. Secondly, a point symmetry-based similarity measure is used to evaluate the similarity between two samples. Finally, both kd-trees-based approximate nearest neighbor searching and k-nearest-neighbor consistency strategy is used to reduce the computation complexity and improve the clustering accuracy. In the experiments, first of all, four real-life data sets and four synthetic data sets are used to test the performance of PSCSCA. PSCSCA is also compared with multiple existing algorithms in terms of clustering accuracy and convergent speed. In addition, PSCSCA is applied to a real-world application, namely natural image compression, with good performance being obtained.

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Acknowledgments

The authors would like to thank the editor and the reviewers for helpful comments that greatly improved the paper. This work is supported by the National Natural Science Foundation of China under Grant No. 61203303 and No. 61272279, the Provincial Natural Science Foundation of Shaanxi of China (No. 2010JM8030), and the Fundamental Research Funds for the Central Universities (No. K50511020014).

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  1. Key Laboratory of Intelligent Perception and Image Understanding of Ministry of Education of China, Xidian University, Xi’an, 710071, China

    Ruochen Liu, Fei He, Jing Liu, Wenping Ma & Yangyang Li

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  1. Ruochen Liu
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  2. Fei He
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  3. Jing Liu
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  4. Wenping Ma
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Correspondence to Ruochen Liu.

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Liu, R., He, F., Liu, J. et al. A point symmetry-based clonal selection clustering algorithm and its application in image compression. Pattern Anal Applic 17, 633–654 (2014). https://doi.org/10.1007/s10044-013-0344-8

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