A supervised approach to electric tower detection and classification for power line inspection

Carlos Sampedro*, Carol Martinez, Aneesh Chauhan, Pascual Campoy

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference paper

47 Citations (Scopus)

Abstract

Inspection of power line infrastructures must be periodically conducted by electric companies in order to ensure reliable electric power distribution. Research efforts are focused on automating the power line inspection process by looking for strategies that satisfy the different requirements of the inspection: simultaneously detect transmission towers, check for defects, and analyze security distances. Following this direction, this paper proposes a supervised learning approach for solving the tower detection and classification problem, where HOG (Histograms of Oriented Gradients) features are used to train two MLP (multi-layer perceptron) neural networks. 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. In the different evaluations, highly encouraging results were obtained. This shows that a learning-based approach is a promising technique for power line inspection.

Original languageEnglish
Title of host publicationProceedings of the International Joint Conference on Neural Networks
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages1970-1977
Number of pages8
ISBN (Print)9781479914845, 9781479914821
DOIs
Publication statusPublished - 3 Sep 2014
Externally publishedYes
Event2014 International Joint Conference on Neural Networks, IJCNN 2014 - Beijing, China
Duration: 6 Jul 201411 Jul 2014

Publication series

NameProceedings of the International Joint Conference on Neural Networks

Conference

Conference2014 International Joint Conference on Neural Networks, IJCNN 2014
CountryChina
CityBeijing
Period6/07/1411/07/14

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  • Cite this

    Sampedro, C., Martinez, C., Chauhan, A., & Campoy, P. (2014). A supervised approach to electric tower detection and classification for power line inspection. In Proceedings of the International Joint Conference on Neural Networks (pp. 1970-1977). [6889836] (Proceedings of the International Joint Conference on Neural Networks). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/IJCNN.2014.6889836