Natural Image Statistics for Natural Image Segmentation

Heiler, Matthias ; Schnörr, Christoph

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URN: urn:nbn:de:bsz:180-madoc-18049
Document Type: Working paper
Year of publication: 2003
The title of a journal, publication series: None
Publication language: English
Institution: School of Business Informatics and Mathematics > Sonstige - Fakultät für Wirtschaftsinformatik und Wirtschaftsmathematik
MADOC publication series: Veröffentlichungen der Fakultät für Mathematik und Informatik > Institut für Informatik > Technical Reports
Subject: 004 Computer science, internet
Subject headings (SWD): Kanonische Abbildung , Bildsegmentierung
Abstract: Building on recent progress in modeling filter response statistics of natural mages we integrate a statistical model into a variational framework for image segmentation. Incorporated in asound probabilistic distance measure the model drives level sets toward meaningful segment at ions of complex textures and natural scenes. Despite its enhanced descriptive power our approach preserves the efficiency of level set based segmentation since each connected region comprises two model parameters only. We validate the statistical basis of our model on thousands of natural images and demonstrate that our approach outperforms recent variational segment at ion methods based on second-order statistics.
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Das Dokument wird vom Publikationsserver der Universitätsbibliothek Mannheim bereitgestellt.

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