Enhanced Snake algorithm by embedded domain transformation

S. Y. Lam, Chong Sze TONG*

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

2 Citations (Scopus)

Abstract

There have been many attempts to improve the original Snake algorithm by Kass et al. to enhance its ability to locate object boundaries with sharp corners or concave parts. But most of these variants of the Snake model require introducing additional external forces or modifying internal energy terms, all of which necessitate cumbersome fine-tuning by users for optimal performance. In this paper, we present a mathematical formulation for a new algorithm that embeds a domain transformation mapping within the Snake algorithm. The domain transformation step serves to render the object contour more convex and hence is more amenable to be better represented by the Snake contour. Analysis of the new algorithm is carried out which facilitated further enhancements to our technique, rendering a final algorithm that is computationally efficient and is easy and flexible to use. Our approach has been tested with very encouraging experimental results.

Original languageEnglish
Pages (from-to)1566-1574
Number of pages9
JournalPattern Recognition
Volume39
Issue number9
DOIs
Publication statusPublished - Sep 2006

Scopus Subject Areas

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

User-Defined Keywords

  • Active contours
  • Conformal mapping
  • Domain transformation
  • Robust contour detection
  • Snakes

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