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Detection of Line Features in Digital Images of Building Structures
University of Gävle, Faculty of Engineering and Sustainable Development, Department of Industrial Development, IT and Land Management. (Datavetenskap)
University of Gävle, Faculty of Engineering and Sustainable Development, Department of Industrial Development, IT and Land Management. (Datavetenskap)ORCID iD: 0000-0003-0085-5829
2012 (English)In: Proceedings of IADIS International Conference Computer Graphics, Visualization, Computer Vision and Image Processing 2012 (CGVCVIP 2012) / [ed] Yingcai Xiao, 2012, 163-167 p.Conference paper, Published paper (Refereed)
Abstract [en]

This paper describes method for detection of short line segments in digital images. It aims at identifying buildingsin images taken from the ground view. The process starts with the image edge map and is carried out in twodifferent levels. One is to detect long line segments usually stemming from façade edges and building silhouettes.The other one identifies shorter line segments which typically represent architectural details such as windows andentrances. Selected individual connected components in both vertical and horizontal gradient component mapsare used respectively as input to the Hough transform at this level. Our first result shows that this method iscapable of recognizing lines of interest but has also included many randomly oriented lines. The next step will beto eliminate the random line segments and correlate line segments of the two levels to classify high-level features ofbuildings in an image.

Place, publisher, year, edition, pages
2012. 163-167 p.
Keyword [en]
Building images, Gradient edges, Hough transform, Line segment detection
National Category
Computer Vision and Robotics (Autonomous Systems) Computer Engineering
Identifiers
URN: urn:nbn:se:hig:diva-12940Scopus ID: 2-s2.0-84887314410ISBN: 978-972-8939-74-8 (print)OAI: oai:DiVA.org:hig-12940DiVA: diva2:553134
Conference
IADIS International Conference Computer Graphics, Visualization, Computer Vision and Image Processing 2012 (CGVCVIP 2012), Lisbon, Portugal, 21-24 July 2012
Available from: 2012-09-18 Created: 2012-09-18 Last updated: 2015-10-06Bibliographically approved

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CiteExportLink to record
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Cite
Citation style
  • apa
  • harvard-cite-them-right
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • sv-SE
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  • en-US
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  • de-DE
  • Other locale
More languages
Output format
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  • text
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