Morphological gradient applied to new active contour model for color image segmentation

Nguyen Tran Lan Anh, Young Chul Kim, Guee Sang Lee

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

Abstract

In this paper, we propose a novel segmentation algorithm for color images. This method is a combination of edge information with region information and a geometric active contour without re-initialization, called distance regularized level set evolution. The information given by a new edge detector using morphological gradient is more accurate than normal gradient computing methods for color images. And the information of the region containing objects is relied on Chan-Vese minimal variance criterion. With both of these information, the model can have its initial contour that is more flexible to construct anywhere, fast to evolve and quite exact to stop at the boundary of objects. The suggested algorithm has been applied on natural color images with good performance. Some experimental results have shown to compare our model with others with respect to accuracy and computational efficiency.

Original languageEnglish
Title of host publicationProceedings of the 6th International Conference on Ubiquitous Information Management and Communication, ICUIMC'12
DOIs
StatePublished - 2012
Event6th International Conference on Ubiquitous Information Management and Communication, ICUIMC'12 - Kuala Lumpur, Malaysia
Duration: Feb 20 2012Feb 22 2012

Publication series

NameProceedings of the 6th International Conference on Ubiquitous Information Management and Communication, ICUIMC'12

Conference

Conference6th International Conference on Ubiquitous Information Management and Communication, ICUIMC'12
Country/TerritoryMalaysia
CityKuala Lumpur
Period02/20/1202/22/12

Keywords

  • Active contour
  • Color images
  • Morphological gradient
  • Squared local contrast

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