Image recognition method for transmission line based on the DeepLab v3+ deep convolutional network
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TM769;TP751

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    Abstract:

    Image recognition of transmission line is an important part in the automatic inspection process of power equipment. For the problems of traditional line detection methods that requine manual design of target features and poor generalization ability, an image recognition method for transmission line based on deep convolutional network (DeepLab v3+) is presented. Firstly, the DeepLab v3+ network model is applied to realize the preliminary segmentation of the lines. This model can automatically learn line features by multi-layer convolutions, and merge the low-level detailed features with the high-level semantic features through a decoder structure to improve the accuracy of line pixel segmentation. Secondly, in order to refine the segmentation results, the improved minimum point pair method and length threshold method for removing broken and pseudo lines are proposed. Finally, an eight-direction search method is used to extract and number each line. The experimental result shows that the proposed method can better extract lines in the transmission line image.

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History
  • Received:January 10,2021
  • Revised:March 05,2021
  • Adopted:December 07,2020
  • Online: August 11,2021
  • Published: July 28,2021