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

Congresses name: 

IEEE World Congress on Computational Intelligence (IEEE WCCI 2014)


Beijing - China

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.



article_powerline_20jan2014r.pdf663.91 KB