Level Sets and Voronoi based Feature Extraction from any Imagery

Publication: Research - peer-reviewArticle in proceedings – Annual report year: 2012

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Polygon features are of interest in many GEOProcessing applications like shoreline mapping, boundary delineation, change detection, etc. This paper presents a unique new GPU-based methodology to automate feature extraction combining level sets, or mean shift based segmentation together with Voronoi skeletonization, that guarantees the extracted features to be topologically correct. The features thus extracted as object centerlines can be stored as vector maps in a Geographic Information System after labeling and editing. We show application examples on different sources: paper maps, digital satellite imagery, and 2D/3D acoustic images (from hydrographic surveys). The application involving satellite imagery shown in this paper is coastline detection, but the methodology can be easily applied to feature extraction on any king of imagery. A prototype application that is developed as part of this research work.
Original languageEnglish
Title of host publicationGEOProcessing 2012 : The Fourth International Conference on Advanced Geographic Information Systems, Applications, and Services
Number of pages9
Publication date2012
Pages89-97
ISBN (print)978-1-61208-178-6
StatePublished

Conference

ConferenceThe Fourth International Conference on Advanced Geographic Information Systems, Applications, and Services (GEOProcessing 2012)
Number4
CountrySpain
CityValencia
Period30/01/1204/02/12
Internet addresshttp://www.iaria.org/conferences2012/GEOProcessing12.html
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