Segmentation of satellite imagery based on pulse-coupled neural network

Qayyum, A. and Malik, A.S. and Saad, M.N.B.M. and Iqbal, M. (2015) Segmentation of satellite imagery based on pulse-coupled neural network. In: UNSPECIFIED.

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Abstract

Vegetation encroachment under overhead high voltage power lines and its monitoring is a challenging problem for electricity distribution companies. Blackout can occurs if proper monitoring of vegetation is not done. The uninterrupted electric power supply is vital for industries, businesses, and daily life. Therefore, it is mandatory for electricity companies to monitor the vegetation/trees near power lines to avoid the blackouts. Pulse-coupled neural network (PCNN) considered as differently from converntial neural networks used in many signal and image processing applications. The main step to develop the automatic detection of vegetation is performing an image segmentation which is normally used to identify or marking of vegetation from the acquired images. We apply PCNN for image segmentation on satellite images for vegetation monitoring purposes and compared the performance with a thresholding image segmentation method with Pulse coupled neural network. The results show that PCNN produce outperform as compared to the thresholding method in terms of detection accuracy. © 2015 IEEE.

Item Type: Conference or Workshop Item (UNSPECIFIED)
Impact Factor: cited By 2
Uncontrolled Keywords: Electric power systems; Electric utilities; Image processing; Image segmentation; Neural networks; Optical radar; Outages; Satellite imagery; Satellites; Vegetation, Electric power supply; Electricity distribution companies; High-voltage power line; Pulse coupled neural network; Segementation; Signal and image processing; Stereo-image; Thresholding techniques, Stereo image processing
Depositing User: Ms Sharifah Fahimah Saiyed Yeop
Date Deposited: 26 Mar 2022 03:23
Last Modified: 26 Mar 2022 03:23
URI: http://scholars.utp.edu.my/id/eprint/31583

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