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A Supervised Approach to Electric Tower Detection and Classification for Power Line Inspection

Publication
Congresses name: 

IEEE World Congress on Computational Intelligence (IEEE WCCI 2014)

Place: 

Beijing - China

Date: 
2014 July 6-11

 

Inspection of power line infrastructures must be periodically conducted by electric companies in order to ensure reliable electric power distribution.

 

This paper proposes a supervised learning approach for solving the tower detection and classification problem. The first classifier is used for background-foreground segmentation, and the second multi-class MLP is used for classifying within 4 different types of electric towers. A thorough evaluation of the tower detection and classification approach has been carried out on image data from real inspections tasks with different types of towers and backgrounds, that show that a learning-based approach is a promising technique for power line inspection.

 

 

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