Fast texture segmentation based on semi-local region descriptor and active contour driven by the Bhattacharyya distance

  • Shanqing Zhang*
  • , Weibin Xin
  • , Guixu Zhang
  • *Corresponding author for this work

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

1 Scopus citations

Abstract

Based on a texture descriptor which intrinsically defines the geometry of textures using semi-local image information and tools from differential geometry, a fast active contour segmentation model for color texture image is proposed. In this model, we use the popular Bhattacharyya distance between the probability density function (pdf) to design the data fitting term which distinguishes the background and textures of interest. Then, a fast algorithm based on the Split-Bregman method is introduced to extract meaningful objects. Finally, some examples on some challenging images are illustrated to verify the possibility of the proposed model.

Original languageEnglish
Title of host publicationProceedings - 2010 2nd International Conference on Multimedia Information Networking and Security, MINES 2010
Pages35-38
Number of pages4
DOIs
StatePublished - 2010
Event2010 2nd International Conference on Multimedia Information Networking and Security, MINES 2010 - Nanjing, Jiangsu, China
Duration: 4 Nov 20106 Nov 2010

Publication series

NameProceedings - 2010 2nd International Conference on Multimedia Information Networking and Security, MINES 2010

Conference

Conference2010 2nd International Conference on Multimedia Information Networking and Security, MINES 2010
Country/TerritoryChina
CityNanjing, Jiangsu
Period4/11/106/11/10

Keywords

  • Active contour
  • Bhattacharyya flow
  • Geometry of textures
  • Image segmentation
  • Split-Bregman method

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