Automatic Prior Shape Selection for Image Segmentation

Weihong Guo, Jing Qin, Sibel Tari

Research output: Chapter in Book/Report/Conference proceedingChapterpeer-review

3 Scopus citations


Segmenting images with occluded and missing intensity information is still a difficult task. Intensity based segmentation approaches often lead to wrong results. High vision prior information such as prior shape has been proven to be effective in solving this problem. Most existing shape prior approaches assume known prior shape and segmentation results rely on the selection of prior shape. In this paper, we study how to do simultaneous automatic prior shape selection and segmentation in a variational scheme.

Original languageEnglish
Title of host publicationAssociation for Women in Mathematics Series
Number of pages8
StatePublished - 2015

Publication series

NameAssociation for Women in Mathematics Series
ISSN (Print)2364-5733
ISSN (Electronic)2364-5741

Bibliographical note

Publisher Copyright:
© 2015, Springer International Publishing Switzerland & The Association for Women in Mathematics.


  • Base Segmentation Model
  • Data Fidelity Term
  • Image Segmentation
  • Prior Shape
  • Sparse Optimization

ASJC Scopus subject areas

  • General Mathematics
  • Gender Studies


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