Quasi-automatic initialization for parametric active contours

C. Tauber*, H. Batatia, A. Ayache

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

26 Citations (Scopus)


Active contour is a well-known image segmentation technique, commonly used to find object boundaries in images. Its main benefit is its ability to retrieve an ordered collection of points. However, fitting precisely a deformable contour to actual boundaries depends strongly on its initialization and requires adjusting various parameters. This paper presents an original method to initialize quasi-automatically explicit deformable models when segmenting regions that require no change of topology. The proposed method relies on a careful study of the gradient vector flow. Two original concepts are introduced, namely strong and weak divergence centers. The analysis of the properties of these centers leads to establishing a quasi-automatic method to setup an initial curve that will reach all the boundaries of a target region. Results using synthetic and real images are presented, showing the validity of our approach.

Original languageEnglish
Pages (from-to)83-90
Number of pages8
JournalPattern Recognition Letters
Issue number1
Publication statusPublished - 1 Jan 2010


  • Active contours
  • Automatic initialization
  • Gradient vector flow
  • Segmentation

ASJC Scopus subject areas

  • Software
  • Signal Processing
  • Computer Vision and Pattern Recognition
  • Artificial Intelligence


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