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dc.contributor.advisorMills, Steven
dc.contributor.advisorLanglotz, Tobias
dc.contributor.authorBaker, Lewis Chapman
dc.date.available2017-06-08T03:03:29Z
dc.date.copyright2017
dc.identifier.citationBaker, L. C. (2017). Power Line Detection from Mobile Devices (Thesis, Master of Science). University of Otago. Retrieved from http://hdl.handle.net/10523/7344en
dc.identifier.urihttp://hdl.handle.net/10523/7344
dc.description.abstractOverhead power lines are a common structure used to transmit and deliver electricity to consumers. The structures, comprised primarily of power poles and power lines, are frequently upgraded, repaired, and maintained by line workers. Often, this maintenance involves making measurements of the structures. Mobile applications such as LineSmarts can be used for this purpose by making measurements through photographs, but are inconvenient since the conductors must be manually identified in the image. Identifying the power lines is tedious, and an automatic method for finding the power lines would greatly improve the usefulness of this application. Power line detection has been well researched, but the literature only covers power line detection from aerial images, and assumes that the power lines are straight. In images taken from ground-level, this assumption is not always fair, as the power lines can have large amounts of curvature due to wire sag. In this thesis, three methods for detecting power lines in ground-based images are implemented and compared using Hough Transform, and Line Tracing techniques. The algorithms showed positive results, with the Line Tracer detecting 76.7% of power lines in the dataset with 2.13 pixel accuracy.
dc.language.isoen
dc.publisherUniversity of Otago
dc.rightsAll items in OUR Archive are provided for private study and research purposes and are protected by copyright with all rights reserved unless otherwise indicated.
dc.subjectPower
dc.subjectLine
dc.subjectDetection
dc.subjectcomputer vision
dc.subjectpowerline
dc.subjecthough transform
dc.subjectline detection
dc.subjectparabola detection
dc.subjectcurve fitting
dc.subjectimage filtering
dc.titlePower Line Detection from Mobile Devices
dc.typeThesis
dc.date.updated2017-06-08T02:21:02Z
dc.language.rfc3066en
thesis.degree.disciplineComputer Science
thesis.degree.nameMaster of Science
thesis.degree.grantorUniversity of Otago
thesis.degree.levelMasters
otago.interloanno
otago.openaccessAbstract Only
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