Insulator Segmentation Based on Community Detection and Hybrid Feature

  • Yuanpeng Tan
  • Chunyu Deng
  • Aixue Jiang
  • Zhenbing ZhaoEmail author
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 11901)


Image segmentation is an important prerequisite for automatic detection of insulator’s surface defects. It is difficult to remove the interference by using traditional methods to segment insulator from aerial images with wires adhering to insulators, pole tower in a large proportion and complex background. To solve these problems, this paper proposes a segmentation method with complex network community detection and hybrid feature for aerial insulator image segmentation. We implement community segmentation for achieving a higher accuracy by using the similarity between pixels. In this method, the image is segmented into super-pixels, then the features of color and texture are calculated to get hybrid feature. Next, we set up a super-pixel network by calculating Gauss similarity of hybrid feature information. Finally, we use the complex network community detection method to extract the insulator. The experiment results demonstrate the presented method is robust, efficient and accurate.


Insulator Community detection Hybrid feature Super-pixel Complex network Aerial image 


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Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  • Yuanpeng Tan
    • 1
  • Chunyu Deng
    • 1
  • Aixue Jiang
    • 2
  • Zhenbing Zhao
    • 2
    Email author
  1. 1.Artificial Intelligence Application DepartmentChina Electric Power Research InstituteBeijingChina
  2. 2.North China Electric Power UniversityBaodingChina

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