Improved GVF external force based on modified normal flow

Yuhua Yao*, Lixiong Liu, Lejian Liao, Ming Wei, Xueming Yin, Xianglin Yang, Yinghui Li

*Corresponding author for this work

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

Abstract

Active contours are one of the most successful image segmentation methods in image processing and computer vision field. Their main limitations are high noise sensitivity and poor capture range from the target object. One of the most promising approaches for solving these limitations is the gradient vector flow (GVF). However, GVF still has improving space in converging to concavities and noise robustness. Here we propose a novel GVF external force based on modified normal flow for improving contour performance. This novel external force field is insensitive to noises and may converge to concavities. We compared the proposed method with other methods by synthetic images and real medical images. Experimental results illustrated that the proposed method had achieved more accurate segmentation for noise robustness and concavity convergence.

Original languageEnglish
Title of host publication2012 5th International Congress on Image and Signal Processing, CISP 2012
Pages671-674
Number of pages4
DOIs
Publication statusPublished - 2012
Externally publishedYes
Event2012 5th International Congress on Image and Signal Processing, CISP 2012 - Chongqing, China
Duration: 16 Oct 201218 Oct 2012

Publication series

Name2012 5th International Congress on Image and Signal Processing, CISP 2012

Conference

Conference2012 5th International Congress on Image and Signal Processing, CISP 2012
Country/TerritoryChina
CityChongqing
Period16/10/1218/10/12

Keywords

  • active contour
  • gradient vector flow
  • image segmentation
  • normal flow

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