Change search
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • harvard1
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf
Active contour evolved by joint probability classification on Riemannian manifold
Show others and affiliations
2016 (English)In: Signal, Image and Video Processing, ISSN 1863-1703, E-ISSN 1863-1711, Vol. 10, no 7, 1257-1264 p.Article in journal (Refereed) Published
Resource type
Text
Abstract [en]

In this paper, we present an active contour model for image segmentation based on a nonparametric distribution metric without any intensity a priori of the image. A novel nonparametric distance metric, which is called joint probability classification, is established to drive the active contour avoiding the instability induced by multimodal intensity distribution. Considering an image as a Riemannian manifold with spatial and intensity information, the contour evolution is performed on the image manifold by embedding geometric image feature into the active contour model. The experimental results on medical and texture images demonstrate the advantages of the proposed method.

Place, publisher, year, edition, pages
Springer London, 2016. Vol. 10, no 7, 1257-1264 p.
Keyword [en]
Active contour, Image segmentation, Joint probability classification, Nonparametric distribution, Riemannian manifold
National Category
Computer Vision and Robotics (Autonomous Systems)
Identifiers
URN: urn:nbn:se:kth:diva-187086DOI: 10.1007/s11760-016-0891-8ISI: 000382363300010Scopus ID: 2-s2.0-84964010146OAI: oai:DiVA.org:kth-187086DiVA: diva2:928962
Note

QC 20161208

Available from: 2016-05-17 Created: 2016-05-17 Last updated: 2016-12-08Bibliographically approved

Open Access in DiVA

No full text

Other links

Publisher's full textScopus

Search in DiVA

By author/editor
Li, Haibo
By organisation
Media Technology and Interaction Design, MID
In the same journal
Signal, Image and Video Processing
Computer Vision and Robotics (Autonomous Systems)

Search outside of DiVA

GoogleGoogle Scholar

Altmetric score

Total: 105 hits
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • harvard1
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf