A convex and selective variational model for image segmentation

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Spencer, Jack and Chen, Ke (2015) A convex and selective variational model for image segmentation. Communications in Mathematical Sciences, 13 (6). pp. 1453-1472. ISSN 1539-6746 (https://doi.org/10.4310/CMS.2015.v13.n6.a5)

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Abstract

Selective image segmentation is the task of extracting one object of interest from an image, based on minimal user input. Recent level set based variational models have shown to be effective and reliable, although they can be sensitive to initialization due to the minimization problems being nonconvex. This sometimes means that successful segmentation relies too heavily on user input or a solution found is only a local minimizer, i.e. not the correct solution. The same principle applies to variational models that extract all objects in an image (global segmentation); however, in recent years, some have been successfully reformulated as convex optimization problems, allowing global minimizers to be found. There are, however, problems associated with extending the convex formulation to the current selective models, which provides the motivation for the proposal of a new selective model. In this paper we propose a new selective segmentation model, combining ideas from global segmentation, that can be reformulated in a convex way such that a global minimizer can be found independently of initialization. Numerical results are given that demonstrate its reliability in terms of removing the sensitivity to initialization present in previous models, and its robustness to user input.

ORCID iDs

Spencer, Jack and Chen, Ke ORCID logoORCID: https://orcid.org/0000-0002-6093-6623;
  • Item type:Article
    ID code:87909
    Dates:
    Date
    Event
    13 May 2015
    Published
    20 August 2014
    Accepted
    19 August 2013
    Submitted
    Notes:Publisher Copyright: © 2015 International Press. Spencer, Jack and Chen, Ke (2015) A CONVEX AND SELECTIVE VARIATIONAL MODEL FOR IMAGE SEGMENTATION. COMMUNICATIONS IN MATHEMATICAL SCIENCES, 13 (6). pp. 1453-1472., http://dx.doi.org/10.4310/cms.2015.v13.n6.a5
    Subjects:Science > Mathematics
    Department:Faculty of Science > Mathematics and Statistics
    Depositing user: Pure Administrator
    Date deposited:25 Jan 2024 14:20
    Last modified:11 Nov 2024 14:12
    Related URLs:
    URI:https://strathprints.strath.ac.uk/id/eprint/87909
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