High dynamic range optimal fuzzy color image enhancement using Artificial Ant Colony System
Applied Soft Computing
PPSN'06 Proceedings of the 9th international conference on Parallel Problem Solving from Nature
Concave minimum cost network flow problems solved with a colony of ants
Journal of Heuristics
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For a point-based image registration method, point matching is a hard and a computationally intensive task to handle especially when issues of noisy and outlying data have to be considered. In this paper we cast the problem as a combinatorial optimization task and wedescribe a global optimization method to achieve robust point matching and pose estimation for image registration purpose. The basic idea is to use Ant Colony System (ACS) as a population based search strategy to evolve promising starting solutions i.e affine transformations. An appropriate local search inspired from extremal optimization is developed and embedded within the search strategy to refine the solutions found. Experimental results are very promising and show the ability of the method to cope with outliers and to achieverobust pose estimation.