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Advances in Fuzzy Systems
Volume 2008, Article ID 920615, 8 pages
Research Article

A Recursive Fuzzy System for Efficient Digital Image Stabilization

Department of Production and Management Engineering, School of Engineering, Democritus University of Thrace, GR-671 00 Xanthi, Greece

Received 14 March 2008; Accepted 23 May 2008

Academic Editor: Zne-Jung Lee

Copyright © 2008 Nikolaos Kyriakoulis and Antonios Gasteratos. 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.


A novel digital image stabilization technique is proposed in this paper. It is based on a fuzzy Kalman compensation of the global motion vector (GMV), which is estimated in the log-polar plane. The GMV is extracted using four local motion vectors (LMVs) computed on respective subimages in the logpolar plane. The fuzzy Kalman system consists of a fuzzy system with the Kalman filter's discrete time-invariant definition. Due to this inherited recursiveness, the output results into smoothed image sequences. The proposed stabilization system aims to compensate any oscillations of the frame absolute positions, based on the motion estimation in the log-polar domain, filtered by the fuzzy Kalman system, and thus the advantages of both the fuzzy Kalman system and the log-polar transformation are exploited. The described technique produces optimal results in terms of the output quality and the level of compensation.