Dynamic programming based comparison including QuickBird and IKONOS satellite stereo images for monitoring vegetation near power poles
Vegetation encroachment under overhead high voltage power line 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 dail...
| Main Authors: | Qayyum, A., Malik, A.S., Naufal, M., Saad, M., Iqbal, M., Ahmad, R.F., Abdullah, T.A.R.B.T. |
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| Format: | Conference or Workshop Item |
| Institution: | Universiti Teknologi Petronas |
| Record Id / ISBN-0: | utp-eprints.31296 / |
| Published: |
Institute of Electrical and Electronics Engineers Inc.
2014
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| Online Access: |
https://www.scopus.com/inward/record.uri?eid=2-s2.0-84988246841&doi=10.1109%2fICCSCE.2014.7072784&partnerID=40&md5=ed94b733377f14a4f6bda428711b4eb6 http://eprints.utp.edu.my/31296/ |
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| Summary: |
Vegetation encroachment under overhead high voltage power line 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. Many approaches are employed to monitor vegetation/trees near the transmission line poles, but these approaches are more time consuming and expensive. In this paper, we have proposed a novel approach to monitor the vegetation near or under the power poles using satellite stereo images which were acquired using QuickBird and IKONOS satellites. 3D depth of vegetation has been measured using stereo algorithm incorporating dynamic programming. We have also compared the results of QuickBird and IKONOS satellite stereo images. Results showed that QuickBird satellite image performs well as compared to IKONOS using stereo vision global optimization dynamic programming algorithm in terms of accuracy and speed. © 2014 IEEE. |
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