Infrared Image Segmentation Method Based on Fuzzy Clustering with Similarity Thresholding

GUO Feng; ZHENG Lei; GE Huangxu; YAN Biwu; GUO Yifan

Volume 47 Issue 8

Aug. 2022

Turn off MathJax

Article Contents

Article Navigation > Infrared Technology > 2022 > 44(8): 863-869

GUO Feng, ZHENG Lei, GE Huangxu, YAN Biwu, GUO Yifan. Infrared Image Segmentation Method Based on Fuzzy Clustering with Similarity Thresholding[J]. Infrared Technology , 2022, 44(8): 863-869.

Citation:

GUO Feng, ZHENG Lei, GE Huangxu, YAN Biwu, GUO Yifan. Infrared Image Segmentation Method Based on Fuzzy Clustering with Similarity Thresholding[J]. Infrared Technology , 2022, 44(8): 863-869.

GUO Feng, ZHENG Lei, GE Huangxu, YAN Biwu, GUO Yifan. Infrared Image Segmentation Method Based on Fuzzy Clustering with Similarity Thresholding[J]. Infrared Technology , 2022, 44(8): 863-869.

Citation:

GUO Feng, ZHENG Lei, GE Huangxu, YAN Biwu, GUO Yifan. Infrared Image Segmentation Method Based on Fuzzy Clustering with Similarity Thresholding[J]. Infrared Technology , 2022, 44(8): 863-869.

PDF( 1000 KB)

Infrared Image Segmentation Method Based on Fuzzy Clustering with Similarity Thresholding

GUO Feng^1
,,
ZHENG Lei^{2, 3},
GE Huangxu⁴,
YAN Biwu²,
GUO Yifan⁴

1.
State Grid Zhejiang Electric Power Company, Hangzhou 310007, China
2.
Wuhan NARI Limited Liability Company of State Grid Electric Power Research Institute, Wuhan 430074, China
3.
NARI Technology Co., Ltd., Nanjing 211106 China
4.
State Grid Zhejiang Electric Power Company Jiaxing Power Supply Company, Jiaxing 314599, China

Received Date: 2021-01-21
Rev Recd Date: 2021-02-24
Publish Date: 2022-08-20

Abstract

Abstract

This paper presents a fuzzy clustering method based on similarity thresholding to detect an overheating fault region from an infrared image of a transmission line. In this method, the original iteration mechanism of fuzzy clustering was improved and a thresholding fuzzy clustering model was built. Thus, a fuzzy member was utilized to measure the neighboring pixels t by conducting cluster analysis on the object region with local neighboring pixels. This ensured similarity during the clustering of the local neighboring pixels into the cluster center. In addition, the maximum similarity thresholding rule was applied to determine the final thresholding using the strategy of thresholding from top to bottom, thus improving the efficiency of the method in obtaining the final region of interest in the infrared image using fuzzy clustering. Finally, experimental results on infrared images of transmission lines show that the good performance of the proposed method and that the proposed method is suitable for fault detection in transmission lines.
- similarity thresholding,
- fuzzy clustering,
- infrared image,
- neighboring pixels

FullText(HTML)

References(16)

References

[1]	王淼, 杜伟, 孙鸿博, 等. 基于红外图像识别的输电线路故障诊断方法[J]. 红外技术, 2017, 39(4): 383-386. http://hwjs.nvir.cn/article/id/hwjs201704015 WANG Miao, DU Wei, SUN Hongbo, et al. Transmission line fault diagnosis method based on infrared image recognition[J]. Infrared Technology, 2017, 39(4): 383-386. http://hwjs.nvir.cn/article/id/hwjs201704015
[2]	张福, 张建刚, 李庭坚, 等. 基于红外热点的电力缺陷检测方法[J]. 电网与清洁能源, 2018, 34(3): 46-50. doi: 10.3969/j.issn.1674-3814.2018.03.009 ZHANG Fu, ZHANG Jiangang, LI Tingjian, et al. An electrical power fault detection method based on infrared image heating[J]. Power System and Clean Energy, 2018, 34(3): 46-50. doi: 10.3969/j.issn.1674-3814.2018.03.009
[3]	刘云鹏, 裴少通, 武建华. 基于深度学习的输变电设备异常发热点红外图片目标检测方法[J]. 南方电网技术, 2019, 13(2): 27-33. https://www.cnki.com.cn/Article/CJFDTOTAL-NFDW201902006.htm LIU Yunpeng, PEI Shaotong, WU Jianhua. Deep learning based target detection method for abnormal hot spots infrared images of transmission and transformation equipment[J]. Southern Power System Technology, 2019, 13(2): 27-33. https://www.cnki.com.cn/Article/CJFDTOTAL-NFDW201902006.htm
[4]	白梓璇, 高强, 于晓, 等. 基于补体免疫聚类的电力设备红外图像目标提取算法[J]. 激光杂志, 2020, 41(3): 107-112. https://www.cnki.com.cn/Article/CJFDTOTAL-JGZZ202003021.htm BAI Zixuan, GAO Qiang, YU Xiao, et al. Infrared image target extraction method for power equipment based on complement immune clustering[J]. Laser Journal, 2020, 41(3): 107-112. https://www.cnki.com.cn/Article/CJFDTOTAL-JGZZ202003021.htm
[5]	井金剑, 翟春艳, 李书臣, 等. 基于红外图像识别的电气设备故障诊断[J]. 电子设计工程, 2014, 22(12): 171-173. doi: 10.3969/j.issn.1674-6236.2014.12.059 JING Jinjian, ZHAI Chunyan, LI Shuchen, et al. Fault diagnosis of electrical equipment based on infrared image recognition[J]. Electronic Design Engineering, 2014, 22(12): 171-173. doi: 10.3969/j.issn.1674-6236.2014.12.059
[6]	赵庆生, 王雨滢, 王旭平, 等. 基于新型阈值选择方法的变电站红外图像分割[J]. 光学学报, 2019, 39(8): 101-108. https://www.cnki.com.cn/Article/CJFDTOTAL-GXXB201908014.htm ZHAO Qingsheng, WANG Yuying, WANG Xuping, et al. Substation infrared image segmentation based on novel threshold selection method[J]. Acta Optica Sinica, 2019, 39(8): 101-108. https://www.cnki.com.cn/Article/CJFDTOTAL-GXXB201908014.htm
[7]	余成波, 曾亮, 张林. 基于OTSU和区域生长的电气设备多点故障分割[J]. 红外技术, 2018, 40(10): 1008-1012. http://hwjs.nvir.cn/article/id/hwjs201810013 YU Chengbo, ZENG Liang, ZHANG Lin. Multi point fault segmentation of electrical equipment based on OTSU and region growth[J]. Infrared Technology, 2018, 40(10): 1008-1012. http://hwjs.nvir.cn/article/id/hwjs201810013
[8]	王启银, 薛建东, 任新辉. 一种自适应的变电站设备红外图像分割方法[J]. 红外技术, 2016, 38(9): 770-773. http://hwjs.nvir.cn/article/id/hwjs201609010 WANG Qiyin, XUE Jiandong, REN Xinhui. An adaptive segmentation method of substation equipment infrared image[J]. Infrared Technology, 2016, 38(9): 770-773. http://hwjs.nvir.cn/article/id/hwjs201609010
[9]	李唐兵, 胡锦泓. 周求宽. 基于Lévy飞行的改进飞蛾扑火算法优化红外图像分割[J]. 红外技术, 2020, 42(9): 846-854. http://hwjs.nvir.cn/article/id/hwjs202009006 LI Tangbing, HU Jinhong, ZHOU Qiukuan. Improved moth-flame optimization algorithm based on Lévy flight to optimize infrared image segmentation[J]. Infrared Technology, 2020, 42(9): 846-854. http://hwjs.nvir.cn/article/id/hwjs202009006
[10]	王小芳, 毛华敏. 一种复杂背景下的电力设备红外图像分割方法[J]. 红外技术, 2019, 41(12): 1111-1116. http://hwjs.nvir.cn/article/id/hwjs201912004 WANG Xiaofang, MAO Huamin. Infrared image segmentation method for power equipment in complex background[J]. Infrared Technology, 2019, 41(12): 1111-1116. http://hwjs.nvir.cn/article/id/hwjs201912004
[11]	王晓飞, 胡凡奎, 黄硕. 基于分布信息直觉模糊c均值聚类的红外图像分割算法[J]. 通信学报, 2020, 41(5): 120-129. https://www.cnki.com.cn/Article/CJFDTOTAL-TXXB202005013.htm WANG Xiaofei, HU Fankui, HUANG Shuo. Infrared image segmentation algorithm based on distribution information intuitionistic fuzzy c-means clustering[J]. Journal on Communications, 2020, 41(5): 120-129. https://www.cnki.com.cn/Article/CJFDTOTAL-TXXB202005013.htm
[12]	冯振新, 许晓路, 周东国, 等. 基于局部区域聚类的电力设备故障区域提取方法[J]. 电测与仪表, 2020, 57(8): 45-50. https://www.cnki.com.cn/Article/CJFDTOTAL-DCYQ202008008.htm FENG Zhenxin, XU Xiaolu, ZHOU Dongguo. Extraction method of power device fault region based on local clustering algorithm[J]. Electrical Measurement & Instrumentation, 2020, 57(8): 45-50. https://www.cnki.com.cn/Article/CJFDTOTAL-DCYQ202008008.htm
[13]	Mehmet Sezgin, Bülent Sankur. Survey over image thresholding techniques and quantitative performance evaluation[J]. Journal of Electronic Imaging, 2004, 13(1): 146-161.
[14]	ZOU Yaobin, DONG Fangmin, LEI Bangjun. Maximum similarity thresholding[J]. Digital Image Processing, 2014, 28: 120-135
[15]	Bezdek J C. Pattern Recognition with Fuzzy Objective Function Algorithm[M]. New York: Springer, 1981.
[16]	Ahmed M N, Yamany S M, Mohamed N, et al. A modified fuzzy c-means algorithm for bias field estimation and segmentation of MRI data[J]. IEEE Transactions on Medical Imaging, 2002, 21: 193-199. doi: 10.1109/42.996338