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  4. Contour based split and merge segmentation and pre-classification of zooplankton in very large images
 
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2014
Conference Paper
Title

Contour based split and merge segmentation and pre-classification of zooplankton in very large images

Abstract
Zooplankton is an important component in the water ecosystem and food chain. To understand the influence of zooplankton on the ecosystem a data collection is necessary. In research the automatic image based recognition of zooplankton is of growing interest. Several systems have been developed for zooplankton recognition on low resolution images. For large images approaches are seldom. Images of this size easily exceed the main memory of standard computers. Our novel automatic segmentation approach is able to handle these large images. We developed a contour based Split & Merge approach for segmentation and, to reduce the nonzooplankton segments, combine it with a pre-classification of the segments in reference to their shape. The latter includes a detection of quasi round segments and a novel one for thin segments. Experimental results on several large images show that we are able to handle them satisfactorily.
Author(s)
Gutzeit, Enrico
Fraunhofer-Institut für Graphische Datenverarbeitung IGD  
Scheel, Christian
Univ. Rostock
Dolereit, Tim  orcid-logo
Fraunhofer-Institut für Graphische Datenverarbeitung IGD  
Rust, Matthias
Arivis AG
Mainwork
9th International Conference on Computer Vision, Theory and Applications 2014. Proceedings. Vol.1  
Conference
International Conference on Computer Vision Theory and Applications (VISAPP) 2014  
International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (VISIGRAPP) 2014  
Open Access
File(s)
Download (1.26 MB)
DOI
10.5220/0004648604170424
10.24406/publica-r-383918
Language
English
Fraunhofer-Institut für Graphische Datenverarbeitung IGD  
Keyword(s)
  • automatic segmentation

  • image segmentation

  • large scale image handling

  • classification methods

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