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Figure-Ground Segmentation using Tabu Search

M. Stricker and A. Leonardis
Proc. of the IEEE Intern. Symposium on Computer Vision
November 1995

Abstract

Many computer vision problems, such as figure-ground segmentation, simultaneous fitting of curves, selection of an optimal set of geometric primitives, can be formulated naturally as discrete optimization problems. The statement of these problems is relatively easy, but to find techniques that efficiently solve them constitutes a major challenge. In this paper we focus on figure-ground segmentation. We present a Tabu search strategy which is able to solve the discrete optimization problem associated with figure-ground segmentation in a very efficient way. The resulting deterministic algorithm outperforms the currently fastest known algorithm to solve this problem (mean field annealing) by two orders of magnitude in speed and in addition it consistently finds better optima.


Download in postscript format
@InProceedings{eth_biwi_00058,
  author = {M. Stricker and A. Leonardis},
  title = {Figure-Ground Segmentation using Tabu Search},
  booktitle = {Proc. of the IEEE Intern. Symposium on Computer Vision},
  year = {1995},
  month = {November},
  pages = {605-610},
  keywords = {optimization, segmentation, edges}
}