Locating object contours in complex background using improved snakes

Authors:
Frank Y. Shih;Kai Zhang
Affiliations:
Computer Vision Laboratory, College of Computing Sciences, New Jersey Institute of Technology, Newark, NJ 07102, USA;Computer Vision Laboratory, College of Computing Sciences, New Jersey Institute of Technology, Newark, NJ 07102, USA
Venue:
Computer Vision and Image Understanding
Year:
2007

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Abstract

An active contour model, called snake, can adapt to object boundary in an image. A snake is defined as an energy minimizing spline guided by external constraint forces and influenced by image forces that pull it toward features such as lines or edges. The traditional snake model fails to locate object contours that appear in complex background. In this paper, we present an improved snake model associated with new regional similarity energy and a gravitation force field to attract the snake approaching the object contours efficiently. Experiment results show that our snake model works successfully for convex and concave objects in a variety of complex backgrounds.