Ant Colony Optimization towards Image Processing

Soft Computing refers to the techniques of problem solving which are inspired from the human behavior, natural genetics and the behavior of insects. All these techniques are parallel computational techniques which aim to handle imprecise, incomplete, non-linear and complex data. This paper deals with one of the fields of soft computing- namely Ant Colony Optimization (ACO). ACO is a computational intelligence based approach which is used to solve combinatorial optimization problem. Due to its simplicity and optimal approach it has been applied to routing, scheduling, sub-set, assignment and classification problems.Focus of the current paper is onto the use of Ant Colony Optimization in the field of Image Processing. Edge detection, edge linking, feature extraction, segmentation and image compression are the various image processing tasks in which ACO has been applied successfully. The details pertaining to each of the approach have been discussed. Benefits of using ACO over the conventional techniques have also been presented.