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Target Classification by Constructing Fuzzy Automata System

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Abstract

This paper will present a target classification system based on fuzzy automata to carry out better target classification, which deal with images first and then classify the objects. The system includes image preprocessing, feature extraction, target matching and classification. Compared with other existing methods, this paper utilizes the characteristics of aurora images and uses fuzzy automata to implement target classification. The simulation results show that the classification effect of the proposed method based on fuzzy automata is better than that of other classification methods. The correct classification rate is 94.66%, and its classification speed is 2.28 s.

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Acknowledgements

This work is supported by Henan Province Outstanding Youth on Science and Technology Innovation (No. 164100510017); National 973 Program (No. 613237); National Natural Science Foundation of China (Nos. 61501407, 61503173), respectively.

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Authors and Affiliations

  1. National Engineering Laboratory for Highway Maintenance Equipment, Chang’an University, Xi’an, 710064, People’s Republic of China

    Ziyu Gao

  2. School of Electrical and Information Engineering, Zhengzhou University of Light Industry, Zhengzhou, 450002, People’s Republic of China

    QingE Wu, Hu Chen, Xiaoliang Qian, Yonghua Wang & Huanlong Zhang

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  1. Ziyu Gao
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  2. QingE Wu
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  3. Hu Chen
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  4. Xiaoliang Qian
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  5. Yonghua Wang
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  6. Huanlong Zhang
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Correspondence to QingE Wu.

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Gao, Z., Wu, Q., Chen, H. et al. Target Classification by Constructing Fuzzy Automata System. Int. J. Fuzzy Syst. 20, 2620–2631 (2018). https://doi.org/10.1007/s40815-018-0494-3

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  • DOI: https://doi.org/10.1007/s40815-018-0494-3

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