Infrared Technology, Volume. 44, Issue 7, 709(2022)

PCNN Infrared Fault Region Detection Along Transmission Lines Based on the MST Framework

Huangxu GE1、*, Lei ZHENG2,3, Hong JIANG1, Yifan GUO1, and Dongguo ZHOU4
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  • 1[in Chinese]
  • 2[in Chinese]
  • 3[in Chinese]
  • 4[in Chinese]
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    References(6)

    [1] [1] Jadin M S, Taib S. Recent progress in diagnosing the reliability of electrical equipment by using infrared thermography[J]. Infrared Physics & Technology, 2012, 55(4): 236-245.

    [12] [12] GUO Zhengkun, SONG Yong, ZHAO Yufei, et al. An adaptive infrared image segmentation method based on fusion SPCNN[J]. Signal Processing: Image Communication, 2020, 87(115905): 1-9.

    [13] [13] TANG Qingju, GAO Shuaishuai, LIU Yongjie, et al. Infrared image segmentation algorithm for defect detection based on FODPSO[J]. Infrared Physics and Technology, 2020, DOI: 10.1016/j.image.2020.115905.

    [14] [14] ZHOU Dongguo, ZHOU Hong. Minimisation of local within-class variance for image segmentation[J]. IET Image Processing, 2016, 10(8): 608-615.

    [15] [15] ZOU Yaobin, DONG Fangmin, LEI Bangjun. Maximum similarity thresholding[J]. Digital Image Processing, 2014, 28: 120-135

    [17] [17] Kuntimad G, Ranganath H S. Perfect image segmentation using pulse coupled neural networks.[J]. IEEE Transactions on Neural Networks, 1999, 10(3): 591-598.

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    GE Huangxu, ZHENG Lei, JIANG Hong, GUO Yifan, ZHOU Dongguo. PCNN Infrared Fault Region Detection Along Transmission Lines Based on the MST Framework[J]. Infrared Technology, 2022, 44(7): 709

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    Paper Information

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    Received: Jan. 2, 2019

    Accepted: --

    Published Online: Aug. 2, 2022

    The Author Email: Huangxu GE (329101854@qq.com)

    DOI:

    CSTR:32186.14.

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