Infrared Technology, Volume. 47, Issue 2, 235(2025)

Superpixel-Based Improved Fuzzy C-Means Clustering for Electrical Equipment Infrared Image Segmentation

Xiaojun WU, Xianzhe YU*, Peng WANG, He ZHAO, and Tiancheng LI
Author Affiliations
  • School of Mechanical and Electrical Engineering, Xi'an University of Architecture and Technology, Xi'an 710055, China
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    References(9)

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    [8] [8] GUO H, CHEN P, HUANG S, et al. A threshold segmentation method for non-uniform illumination image based on brightness equalization[J]. IOP Conference Series: Materials Science and Engineering, 2019, 569: 052046.

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    [16] [16] WANG Qingsheng, WANG Xiaopeng, FANG Chao, et al. Robust fuzzy c-means clustering algorithm with adaptive spatial & intensity constraint and membership linking for noise image segmentation[J]. Applied Soft Computing Journal, 2020, 92: 106318.

    [17] [17] LEI Tao, JIA Xiaohong, ZHANG Yanning, et al. Significantly fast and robust fuzzy C-Means clustering algorithm based on morphological reconstruction and membership filtering[J]. IEEE Transactions on Fuzzy Systems, 2018, 26(5): 3027- 3041.

    [18] [18] LEI Tao, JIA Xiaohong, ZHANG Yanning, et al. Superpixel-based fast fuzzy C-Means clustering for color image segmentation[J]. IEEE Trans. Fuzzy Systems, 2019, 27(9): 1753-1766.

    [19] [19] ACHANTA R, SUSSTRANK S. Superpixels and polygonsusing simple non-iterative clustering[C]//2017 IEEE Conference on Computer Vision and Pattern Recognition, 2017: 4895-4904.

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    WU Xiaojun, YU Xianzhe, WANG Peng, ZHAO He, LI Tiancheng. Superpixel-Based Improved Fuzzy C-Means Clustering for Electrical Equipment Infrared Image Segmentation[J]. Infrared Technology, 2025, 47(2): 235

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    Paper Information

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    Received: Jul. 22, 2022

    Accepted: Mar. 13, 2025

    Published Online: Mar. 13, 2025

    The Author Email: YU Xianzhe (fisher19970628@163.com)

    DOI:

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