Cellular Automata on FPGAs for Image Processing

Abstract

Cellular automata (CA) are computational models of physical systems, where space and time are discrete and interactions are local. Specific CA attributes make them ideal for designing complex electronic circuits for the automated image processing. In terms of circuit design and layout, ease of mask generation, silicon-area utilization, and maximization of clock speed, CAs are perhaps one of the most suitable computational structures for hardware realization. In this paper, we present a computational tool designed to create specialized FPGAs that achieve automated image processing such as noise filtering, edge thinning and convex hull detection. The user of the tool specifies the initial parameters and the automation design tool returns the VHDL code needed for the dedicated electronic circuit. Testing the tool using various initial conditions showed that the corresponding CA algorithms have been successfully implemented into hardware.