An Efficient Active Contour Model Through Curvature Scale Space Filtering

  • Authors:

  • Farahnaz Mohanna;Farzin Mokhtarian

  • Affiliations:

  • Centre for Vision, Speech, and Signal Processing, Department of Electronic and Electrical Engineering, University of Surrey, Guildford, England GU2 7XH, UK. F.Mohanna@ee.surrey.ac.ukF.Mokhtarian@ee.surrey.ac.uk

  • Venue:
  • Multimedia Tools and Applications
  • Year:
  • 2003

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Abstract

Active contour models can be successfully used in multimedia database retrieval systems if they have good accuracy and high speed. The majority of existing active contour models do not lock on to interest objects very accurately and quickly especially in complex images. The behavior of the active contour is generally controlled by its internal and external energies. Internal energy is composed of two parts; the first part acts to shorten the active contour as it iterates towards the interest object, while the second part is the curvature of the active contour and forces smoothness of active contour during its movement towards interest object. In this paper, first a reformulated internal energy is proposed to improve the computation of curvature at point vi by making use of the three points vi − 1, vi and vi + 1. Second, an accurate and high speed active contour model, SAC is proposed based on reformulating internal energy by removing the curvature part and using Gaussian filtering with low scale of smoothing. The SAC model has only one parameter that affects the internal energy of active contour and as a result of using the Curvature Scale Space (CSS)1 technique for smoothing, the SAC model is more independent of model parameter setting and the initial snake.