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Improved combined invariant moment for moving targets classification

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Abstract

Invariant moment is a highly concentrated and distortion invariant image features. The goal of multi-moving object characterization and classification methods is to find a suitable description of different kinds of moving objects in the scene and match the similarity between unknown moving objects with invariant moment. This paper presents evolution and development of invariant moments family history, and designs a classification model to classify multi-moving objects. Experimental results show that this method can effectively improve the recognition rate of the moving object.

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Acknowledgments

This research has partially been supported by theproject funded of the Department of Transportation Informatization under Grant No. 2013-364-836-900, National Natural Science Foundation of China under Grant No. 71573107, 71471077, 41374129, 41474095, 60673190, 61502206, 61502208 and 61203244, Science Foundation of Jiangsu Province under Grant No. BK20150522 and BK20150523, College Natural Science Research of Jiangsu Province under Grant No. 14KJB520008, Senior Technical Personnel of Scientific Research Fund of Jiangsu University under Grant No. 13JDG126, Nature Science Foundation of Jiangsu Province under Grant No.SBK2015040772, Research Innovation Program for College Graduates of Jiangsu Province under Grant No. KYLX15_1078.

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Authors and Affiliations

  1. Information Department, Affiliated Hospital of Jiangsu University, Jiangsu University, Jiefang Road No. 438, Zhenjiang, Jiangsu, China, 212001

    Xiao-jun Chen, Bao-ding Chen, Hui Xu & Jian-guo Zhang

  2. School of Computer Science and Communication Engineering, JiangSu University, Zhenjiang, Jiangsu, China

    Xiao-jun Chen, Jia Ke, Yong-zhao Zhan, Qian-qian Zhang & Xiao-ming Jiang

  3. School of Management, Jiangsu University, Zhenjiang, Jiangsu, China

    Jia Ke & Xin-ping Song

  4. Automotive Engineering Research Institute, Jiangsu University, Zhenjiang, Jiangsu, China

    Xiao-bo Chen & Xiao-ming Jiang

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  1. Xiao-jun Chen
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  2. Jia Ke
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  3. Yong-zhao Zhan
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  9. Hui Xu
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  10. Jian-guo Zhang
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Correspondence to Xiao-jun Chen.

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Chen, Xj., Ke, J., Zhan, Yz. et al. Improved combined invariant moment for moving targets classification. Multimed Tools Appl 76, 19959–19982 (2017). https://doi.org/10.1007/s11042-016-4014-x

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  • DOI: https://doi.org/10.1007/s11042-016-4014-x

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