A tabu search method for geometric primitive extraction

In this paper, we propose a novel method for extracting the geometric primitives from geometric data, which is essentially an optimization problem. Specifically, we use tabu search to solve geometric primitive extraction problem. To the Ž . best of our knowledge, it is the first attempt that tabu search is used in computer vision. Our tabu search TS has a number Ž . Ž . of advantages: 1 TS avoids entrapment in local minima and continues the search to give a near-optimal final solution; 2 Ž . Ž . Ž . TS is very general and conceptually much simpler than either simulated annealing SA or genetic algorithm GA ; 3 TS Ž . Ž . has no special space requirement and is very easy to implement the entire procedure only occupies a few lines of code ; 4 our TS-based method can successfully extract some geometric primitives which are specially difficult for the traditional Ž . Ž . methods such as Hough Transform HT and Robust Statistics RS . TS is a flexible framework of a variety of strategies originating from artificial intelligence and is therefore open to further improvement. q 1997 Published by Elsevier Science