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Pixel Coverage Segmentation for Improved Feature Estimation
Faculty of Engineering, University of Novi Sad, Serbia.
Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Centre for Image Analysis. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis.
2009 (English)In: 15th International Conference on Image Analysis and Processing: ICIAP 2009 / [ed] Pasquale Foggia, Carlo Sansone, Mario Vento, Berlin / Heidelberg: Springer , 2009, 929-938 p.Conference paper, Published paper (Refereed)
Abstract [en]

By utilizing intensity information available in images, partial coverage of pixels at object borders can be estimated. Such information can, in turn, provide more precise feature estimates. We present a pixel coverage segmentation method which assigns pixel values corresponding to the area of a pixel that is covered by the imaged object(s). Starting from any suitable crisp segmentation, we extract a one-pixel thin 4-connected boundary between the observed image components where a local linear mixture model is used for estimating fractional pixel coverage values. We evaluate the presented segmentation method, as well as its usefulness for subsequent precise feature estimation, on synthetic test objects with increasing levels of noise added. We conclude that for reasonable noise levels the presented method outperforms the achievable results of a perfect crisp segmentation. Finally, we illustrate the application of the suggested method on a real histological colour image.

 

Place, publisher, year, edition, pages
Berlin / Heidelberg: Springer , 2009. 929-938 p.
Series
Lecture Notes in Computer Science, ISSN 0302-9743 ; 5716
National Category
Computer Vision and Robotics (Autonomous Systems)
Identifiers
URN: urn:nbn:se:uu:diva-111208DOI: 10.1007/978-3-642-04146-4_99ISBN: 978-3-642-04145-7 (print)OAI: oai:DiVA.org:uu-111208DiVA: diva2:279812
Conference
International Conference on Image Analysis and Processing
Available from: 2009-12-07 Created: 2009-12-07 Last updated: 2010-03-01Bibliographically approved

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Computer Vision and Robotics (Autonomous Systems)

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CiteExportLink to record
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  • apa
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Language
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  • nn-NO
  • nn-NB
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Output format
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  • text
  • asciidoc
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