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Exact evaluation of...
Exact evaluation of stochastic watersheds : From trees to general graphs
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- Malmberg, Filip (författare)
- Swedish University of Agricultural Sciences,Sveriges lantbruksuniversitet,Uppsala universitet,Avdelningen för visuell information och interaktion,Bildanalys och människa-datorinteraktion,Centrum för bildanalys,Centre for Image Analysis
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- Selig, Bettina (författare)
- Swedish University of Agricultural Sciences,Sveriges lantbruksuniversitet,Uppsala universitet,Avdelningen för visuell information och interaktion,Bildanalys och människa-datorinteraktion,Centrum för bildanalys,Centre for Image Analysis
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- Luengo Hendriks, Cris L. (författare)
- Uppsala universitet,Avdelningen för visuell information och interaktion,Bildanalys och människa-datorinteraktion
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(creator_code:org_t)
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- ISBN 9783319099545
- Berlin, Heidelberg : Springer Berlin/Heidelberg, 2014
- 2014
- Engelska.
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Ingår i: Discrete Geometry for Computer Imagery. - Berlin, Heidelberg : Springer Berlin/Heidelberg. - 9783319099545 ; 8668, s. 309-319
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https://doi.org/10.1...
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Innehållsförteckning
Abstract
Ämnesord
Stäng
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- The stochastic watershed is a method for identifying salient contours in an image, with applications to image segmentation. The method computes a probability density function (PDF), assigning to each piece of contour in the image the probability to appear as a segmentation boundary in seeded watershed segmentation with randomly selected seedpoints. Contours that appear with high probability are assumed to be more important. This paper concerns an efficient method for computing the stochastic watershed PDF exactly, without performing any actual seeded watershed computations. A method for exact evaluation of stochastic watersheds was proposed by Meyer and Stawiaski (2010). Their method does not operate directly on the image, but on a compact tree representation where each edge in the tree corresponds to a watershed partition of the image elements. The output of the exact evaluation algorithm is thus a PDF defined over the edges of the tree. While the compact tree representation is useful in its own right, it is in many cases desirable to convert the results from this abstract representation back to the image, e. g, for further processing. Here, we present an efficient linear time algorithm for performing this conversion.
Ämnesord
- NATURVETENSKAP -- Data- och informationsvetenskap -- Datorseende och robotik (hsv//swe)
- NATURAL SCIENCES -- Computer and Information Sciences -- Computer Vision and Robotics (hsv//eng)
- NATURVETENSKAP -- Data- och informationsvetenskap -- Datavetenskap (hsv//swe)
- NATURAL SCIENCES -- Computer and Information Sciences -- Computer Sciences (hsv//eng)
Nyckelord
- stochastic watershed
- watershed cut
- minimum spanning tree
Publikations- och innehållstyp
- ref (ämneskategori)
- kon (ämneskategori)
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