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- aggregation classification "P1".
- aggregation creator person.
- aggregation creator person.
- aggregation creator person.
- aggregation date "2011".
- aggregation format "application/pdf".
- aggregation hasFormat 1226980.bibtex.
- aggregation hasFormat 1226980.csv.
- aggregation hasFormat 1226980.dc.
- aggregation hasFormat 1226980.didl.
- aggregation hasFormat 1226980.doc.
- aggregation hasFormat 1226980.json.
- aggregation hasFormat 1226980.mets.
- aggregation hasFormat 1226980.mods.
- aggregation hasFormat 1226980.rdf.
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- aggregation hasFormat 1226980.txt.
- aggregation hasFormat 1226980.xls.
- aggregation hasFormat 1226980.yaml.
- aggregation isPartOf urn:isbn:9783642236877.
- aggregation isPartOf urn:issn:0302-9743.
- aggregation language "eng".
- aggregation publisher "Springer".
- aggregation rights "I have transferred the copyright for this publication to the publisher".
- aggregation subject "Technology and Engineering".
- aggregation title "Robust active contour segmentation with an efficient global optimizer".
- aggregation abstract "Active contours or snakes are widely used for segmentation and tracking. Recently a new active contour model was proposed, combining edge and region information. The method has a convex energy function, thus becoming invariant to the initialization of the active contour. This method is promising, but has no regularization term. Therefore segmentation results of this method are highly dependent of the quality of the images. We propose a new active contour model which also uses region and edge information, but which has an extra regularization term. This work provides an efficient optimization scheme based on Split Bregman for the proposed active contour method. It is experimentally shown that the proposed method has significant better results in the presence of noise and clutter.".
- aggregation authorList BK146140.
- aggregation endPage "206".
- aggregation startPage "195".
- aggregation volume "6915".
- aggregation aggregates 3052525.
- aggregation isDescribedBy 1226980.
- aggregation similarTo 978-3-642-23687-7_18.
- aggregation similarTo LU-1226980.