A multiphase region-based framework for image segmentation based on least square method

G. Chen*, Xin Meng, T. Hu, X. Y. Guo, Li Xiong Liu, Haiying Zhang

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

1 Citation (Scopus)

Abstract

We propose a multiphase region-based framework for image segmentation using Least Square Method, by piecewise constant optimal approximations. The basic idea of our model is to build up a minimum error functional by approximating n sub-regions of the original image with n constants respectively. The main contribution of our method is that we introduce weighting matrixes into the region-based model, which can enhance the weight of the specific region while reducing the influence from other regions. Moreover, our method can fast converge, and segment a given image into arbitrary regions under least squares and iterative algorithm. Experimental results show the advantages of our method in terms of accuracy and efficiency in image segmentation.

Original languageEnglish
Title of host publication2009 IEEE International Conference on Image Processing, ICIP 2009 - Proceedings
PublisherIEEE Computer Society
Pages4009-4012
Number of pages4
ISBN (Print)9781424456543
DOIs
Publication statusPublished - 2009
Event2009 IEEE International Conference on Image Processing, ICIP 2009 - Cairo, Egypt
Duration: 7 Nov 200910 Nov 2009

Publication series

NameProceedings - International Conference on Image Processing, ICIP
ISSN (Print)1522-4880

Conference

Conference2009 IEEE International Conference on Image Processing, ICIP 2009
Country/TerritoryEgypt
CityCairo
Period7/11/0910/11/09

Keywords

  • Image segmentation
  • Least mean square methods

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