Design of highly parallel edge detection nodes using evolutionary techniques

This paper considers the application of bio-inspired systems in the design of a novel and highly parallel image processing tool to detect edges within conventional grey-scale images. The aim of the work is to implement a new image processing architecture through evolvable hardware that is able to adapt according to the particular images encountered. The simulation of such a system through the use of evolutionary algorithms and genetic programming is demonstrated for the conventional image processing operation of edge detection. Results are presented for this system and evaluated with respect to a conventional Sobel edge detector.