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High Voltage Power Line Detection Based on Intersection Point Algorithm

In this paper, an introduction of the challenge of High Voltage Power Line Detection and some methods about solving the similar problem are talked about. To get a better result, a sort of new methods is developed for detecting and tracking high voltage power lines in the field of high voltage power line inspection by using Unmanned Aerial Vehicle (UAV). With the fast development of automated technology, a solution of real-time detecting and tracking of high voltage power lines can be considered on UAV instead of human work. The usability of Intersection Point Algorithm is the main task for detect the power lines from the preprocessing image.
There are many lines located in the preprocessing image in different directions, which get crossing with each other many times. To eliminate the false lines, some invariant features for Intersection Point Algorithm are needed. The intersection points inside of a small region and quite similar directions can probably be considered as the intersection point of power lines. Therefore, three methods are considered for grouping points, which conform to the features of intersection points of power lines. There should be only one concentrated area, which represents both power lines and heading direction of it. Method one is to select the points based on distance of points. Method two is to select the overlap region of the circles based on overlap layers. And method three is searching the overlapped layers by using Sliding Window.
Result evaluation in Project APOLI is done with the Hit, Miss, Fail standard.

Identiferoai:union.ndltd.org:DRESDEN/oai:qucosa:de:qucosa:31765
Date24 September 2018
CreatorsDu, Zijun
ContributorsHardt, Wolfram, Hardt, Wolfram, Tudevdagva, Uranchimeg, Battseren, Batbayar, Technische Universität Chemnitz
Source SetsHochschulschriftenserver (HSSS) der SLUB Dresden
LanguageEnglish
Detected LanguageEnglish
Typeinfo:eu-repo/semantics/acceptedVersion, doc-type:masterThesis, info:eu-repo/semantics/masterThesis, doc-type:Text
Rightsinfo:eu-repo/semantics/openAccess

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