A GP Artificial Ant for image processing: preliminary experiments with EASEA.

This paper describes how animat-based “food foraging” techniques may be applied to the design of low-level image processing algorithms. First, we show how we implemented the food foraging application using the EASEA software package. We then use this technique to evolve an animat and learn how to move inside images and detect high-gradient lines with a minimum exploration time. The resulting animats do not use standard “scanning + filtering” techniques but develop other image exploration strategies close to contour tracking. Experimental results on grey level images are presented.