Active contours: Generalization of the snake mode

Avishay Meron, Zivan Paz, Guy Barnhart-Magen, Gady Golan

Research output: Contribution to journalArticlepeer-review


Segmentation is one of the fundamental issues in the field of image processing and computer vision. Various approaches include differentiating an object in the image as a final goal or for further processing (medical diagnosis, surveillance, 3-D reconstruction and more). Snakes, a model proposed by Kass, Witkin, and Terzopoulos in 1987, provides an efficient method for segmenting an object through the minimization of its energy. The advantage of snakes is in its ability to use high-level data given by the algorithm operator, as opposed to other methods such as the Laplace technique. The snakes model inherently imposes strong constraints on a given image in order to successfully segment an object. In this paper, the use of adjustment methods is described, which allow us to generalize the snake model to a wider range of applications. Through the use of pre-processing techniques, the model's constraints were softened. The main theoretical model and its use in facing a real life image is presented.

Original languageEnglish
Pages (from-to)249-256
Number of pages8
JournalJournal of the Society for Information Display
Issue number3
StatePublished - Mar 2010
Externally publishedYes


  • Image processing
  • Mathematical rubber
  • Object contours
  • Segmentation of objects
  • Snake


Dive into the research topics of 'Active contours: Generalization of the snake mode'. Together they form a unique fingerprint.

Cite this