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J Environ Manage. 2018 Jan 15;206:1233-1242. doi: 10.1016/j.jenvman.2017.09.036. Epub 2017 Sep 18.

Detection of the power lines in UAV remote sensed images using spectral-spatial methods.

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Department of Electronics and Communication Engineering, NIT Srinagar, Hazratbal Road, Srinagar, Jammu and Kashmir, 190006, India.
Department of Aerospace Engineering, Indian Institute of Science, Bangalore, 560012, India.
Robotics Advance Lab, School of Electrical and Electronic Engineering, Nanyang Technological University, 50 Nanyang Avenue, 639798, Singapore. Electronic address:


In this paper, detection of the power lines on images acquired by Unmanned Aerial Vehicle (UAV) based remote sensing is carried out using spectral-spatial methods. Spectral clustering was performed using Kmeans and Expectation Maximization (EM) algorithm to classify the pixels into the power lines and non-power lines. The spectral clustering methods used in this study are parametric in nature, to automate the number of clusters Davies-Bouldin index (DBI) is used. The UAV remote sensed image is clustered into the number of clusters determined by DBI. The k clustered image is merged into 2 clusters (power lines and non-power lines). Further, spatial segmentation was performed using morphological and geometric operations, to eliminate the non-power line regions. In this study, UAV images acquired at different altitudes and angles were analyzed to validate the robustness of the proposed method. It was observed that the EM with spatial segmentation (EM-Seg) performed better than the Kmeans with spatial segmentation (Kmeans-Seg) on most of the UAV images.


Spatial segmentation; Spectral clustering; Unmanned aerial vehicle

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