CNN applications from the hardware point of view: video sequence segmentation: Research Articles

Authors:
Asko Kananen;Ari Paasio;Mika Laiho;Kari Halonen
Affiliations:
Electronic Circuit Design Laboratory, Helsinki University of Technology, P.O. Box 3000, HUT-02015, Finland;Electronic Circuit Design Laboratory, Helsinki University of Technology, P.O. Box 3000, HUT-02015, Finland;Electronic Circuit Design Laboratory, Helsinki University of Technology, P.O. Box 3000, HUT-02015, Finland;Electronic Circuit Design Laboratory, Helsinki University of Technology, P.O. Box 3000, HUT-02015, Finland
Venue:
International Journal of Circuit Theory and Applications - CNN Technology
Year:
2002

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Abstract

In this paper, the problems present in hardware implementations of cellular non-linear network (CNN) type parallel processors are discussed. Instead of designing a multipurpose processor, or even a full image size application specific parallel processor, we suggest a division of the processing task into categories depending on the cell dynamics and on the spread of the influence of a cell. In this way, drastic savings can be achieved in silicon size and in processing speed. As an example, we use a CNN algorithm that was designed for video image segmentation for object-based compression of video signal. We start with discussion of the problems related to implementation of the algorithm with current multipurpose processors. We then introduce hardware structures that can be used in obtaining certain functionalities. In the same section, we also deal with the division of the processing task. We also compare the introduced hardware solution for the algorithm with multipurpose processor structures in silicon size, power consumption and in processing speed. Copyright © 2002 John Wiley & Sons, Ltd.