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ISRN Machine Vision
Volume 2012 (2012), Article ID 152601, 7 pages
http://dx.doi.org/10.5402/2012/152601
Research Article

An Artificial Cellular Convolution Architecture for Real-Time Image Processing

1Griffith School of Engineering, Griffith University, Nathan Campus, Nathan, QLD 4111, Australia
2Machine Intelligence Group, School of Computer Science, Indian Institute of Information Technology and Management-Kerala, Technopark Campus, Thiruvananthapuram 695581, India

Received 20 July 2011; Accepted 28 August 2011

Academic Editors: J. Alvarez-Borrego and S. J. Horng

Copyright © 2012 H. Mahrous and A. P. James. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Abstract

An artificial cell is comprised of the most basic elements in a hierarchical system, that has minimal functionality, but general enough to obey the rules of “artificial life.” The ability to replicate, organize hierarchy, and generalize within an environment is some of the properties of an artificial cell. We present a hardware artificial cell having the properties of generalization ability, the ability of self-organization, and the reproducibility. The cells are used in parallel hardware architecture for implementing the real-time 2D image convolution operation. The proposed hardware design is implemented on FPGA and tested on images. We report improved processing speeds and demonstrate its usefulness in an image filtering application.