Optimal structuring element extraction for MST-based shapes description using tabu search

In this paper, we propose a novel method for extracting the optimal structure element for MST-based shape description. Specifically, we use tabu search to solve the optimal structure element extraction problem for morphological signature transform (MST)-based shape description. To the best of our knowledge, this is the first attempt in which tabu search has been used in computer vision. Our tabu search (TS) has a number of advantages: (1) TS avoids entrapment in local minima and continues the search to give a near-optimal final solution; (2) TS is very general and conceptually much simpler than either simulated annealing or genetic algorithms; (3) TS is very easy to implement and the entire procedure only occupies a few lines of code; (4) TS is a flexible framework of a variety of strategies originating from artificial intelligence and is therefore open to further improvement