A new image segmentation and smoothing model

Song Gao, Tien D. Bui

Research output: Chapter in Book/Report/Conference proceedingConference contribution

11 Scopus citations

Abstract

In this paper, we develop a new segmentation and smoothing model which has many advantages compared to Chan and Vese's active contours model. In our method, the curve evolution partial differential equations (PDEs) for different level set functions are decoupled and solved separately. This decoupling of the motion equations of the level set functions not only speeds up the segmentation process significantly, it also removes the difficulties associated with the initialization of the level sets in Chan and Vese's method. The proposed method can avoid the initial condition problem. Finally, we use in this paper the diffusion equation for denoising and therefore it can deal with very noisy images.

Original languageEnglish (US)
Title of host publication2004 2nd IEEE International Symposium on Biomedical Imaging
Subtitle of host publicationMacro to Nano
Pages137-140
Number of pages4
StatePublished - 2004
Externally publishedYes
Event2004 2nd IEEE International Symposium on Biomedical Imaging: Macro to Nano - Arlington, VA, United States
Duration: Apr 15 2004Apr 18 2004

Publication series

Name2004 2nd IEEE International Symposium on Biomedical Imaging: Macro to Nano
Volume1

Other

Other2004 2nd IEEE International Symposium on Biomedical Imaging: Macro to Nano
Country/TerritoryUnited States
CityArlington, VA
Period4/15/044/18/04

ASJC Scopus subject areas

  • General Engineering

Fingerprint

Dive into the research topics of 'A new image segmentation and smoothing model'. Together they form a unique fingerprint.

Cite this