Regular Articles

Level set method for image segmentation based on moment competition

[+] Author Affiliations
Hai Min, Jing Jin, Hong-Zhi Wang, Hai Li

Chinese Academy of Sciences, Hefei Institutes of Physical Science, Center of Medical Physics and Technology & Cancer Hospital, No. 350 Shushanhu Road, Hefei, Anhui 230031, China

Xiao-Feng Wang

Hefei University, Department of Computer Science and Technology, Key Lab of Network and Intelligent Information Processing, No. 99 Jinxiu Road, Hefei, Anhui 230601, China

De-Shuang Huang

Tongji University, Machine Learning and Systems Biology Laboratory, No. 4800 Caoangong Road, Shanghai 201804, China

J. Electron. Imaging. 24(3), 033020 (Jun 09, 2015). doi:10.1117/1.JEI.24.3.033020
History: Received October 28, 2014; Accepted May 13, 2015
Text Size: A A A

Abstract.  We propose a level set method for image segmentation which introduces the moment competition and weakly supervised information into the energy functional construction. Different from the region-based level set methods which use force competition, the moment competition is adopted to drive the contour evolution. Here, a so-called three-point labeling scheme is proposed to manually label three independent points (weakly supervised information) on the image. Then the intensity differences between the three points and the unlabeled pixels are used to construct the force arms for each image pixel. The corresponding force is generated from the global statistical information of a region-based method and weighted by the force arm. As a result, the moment can be constructed and incorporated into the energy functional to drive the evolving contour to approach the object boundary. In our method, the force arm can take full advantage of the three-point labeling scheme to constrain the moment competition. Additionally, the global statistical information and weakly supervised information are successfully integrated, which makes the proposed method more robust than traditional methods for initial contour placement and parameter setting. Experimental results with performance analysis also show the superiority of the proposed method on segmenting different types of complicated images, such as noisy images, three-phase images, images with intensity inhomogeneity, and texture images.

© 2015 SPIE and IS&T

Citation

Hai Min ; Xiao-Feng Wang ; De-Shuang Huang ; Jing Jin ; Hong-Zhi Wang, et al.
"Level set method for image segmentation based on moment competition", J. Electron. Imaging. 24(3), 033020 (Jun 09, 2015). ; http://dx.doi.org/10.1117/1.JEI.24.3.033020


Access This Article
Sign in or Create a personal account to Buy this article ($20 for members, $25 for non-members).

Some tools below are only available to our subscribers or users with an online account.

Related Content

Customize your page view by dragging & repositioning the boxes below.

Related Book Chapters

Topic Collections

PubMed Articles
Advertisement
  • Don't have an account?
  • Subscribe to the SPIE Digital Library
  • Create a FREE account to sign up for Digital Library content alerts and gain access to institutional subscriptions remotely.
Access This Article
Sign in or Create a personal account to Buy this article ($20 for members, $25 for non-members).
Access This Proceeding
Sign in or Create a personal account to Buy this article ($15 for members, $18 for non-members).
Access This Chapter

Access to SPIE eBooks is limited to subscribing institutions and is not available as part of a personal subscription. Print or electronic versions of individual SPIE books may be purchased via SPIE.org.