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  4. Semi-automatic analysis of huge digital nautical charts of coastal aerial images
 
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2015
Conference Paper
Title

Semi-automatic analysis of huge digital nautical charts of coastal aerial images

Abstract
Geo-referenced aerial images are available in very high resolution. The automated production and updating of electronic nautical charts (ENC), as well as other products (e.g. thematic maps), from aerial images is a current challenge for hydrographic organizations. Often standard vision algorithms are not reliable enough for robust object detection in natural images. We thus propose a procedure that combines processing steps on three levels, from pixel (low-level) via segments (mid-level) to semantic information (high level). We combine simple linear iterative clustering (SLIC) as an efficient low-level algorithm with a classification based on texture features by supported vector machine (SVM) and a generalized Hough transformation (GHT) for detecting shapes on mid-level. Finally, we show how semantic information can be used to improve results from the earlier processing steps in the high-level step. As standard vision methods are typically much too slow for such huge-sized images and additionally geographical references must be maintained over the complete procedure, we present a solution to overcome these problems.
Author(s)
Vahl, Matthias  
Fraunhofer-Institut für Graphische Datenverarbeitung IGD  
Lukas, Uwe von  orcid-logo
Fraunhofer-Institut für Graphische Datenverarbeitung IGD  
Urban, Bodo  
Fraunhofer-Institut für Graphische Datenverarbeitung IGD  
Kuijper, Arjan  orcid-logo
Fraunhofer-Institut für Graphische Datenverarbeitung IGD  
Mainwork
10th International Conference on Computer Vision Theory and Applications, VISAPP 2015. Proceedings. Vol.III  
Conference
International Conference on Computer Vision Theory and Applications (VISAPP) 2015  
International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (VISIGRAPP) 2015  
Open Access
File(s)
Download (9.54 MB)
DOI
10.5220/0005301501000107
10.24406/publica-r-388237
Language
English
Fraunhofer-Institut für Graphische Datenverarbeitung IGD  
Keyword(s)
  • computer vision

  • geographic information systems (GIS)

  • segmentation

  • image analysis

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