A Recursive Fuzzy System for Efficient Digital Image Stabilization | Zendy

Nikolaos Kyriakoulis | Zendy; Αντώνιος Γαστεράτος | Zendy

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A Recursive Fuzzy System for Efficient Digital Image Stabilization

Author(s) -

Nikolaos Kyriakoulis,

Αντώνιος Γαστεράτος

Publication year - 2008

Publication title -

advances in fuzzy systems

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 0.38

H-Index - 19

eISSN - 1687-711X

pISSN - 1687-7101

DOI - 10.1155/2008/920615

Subject(s) - kalman filter , fuzzy logic , computer vision , polar coordinate system , control theory (sociology) , artificial intelligence , fuzzy control system , computer science , transformation (genetics) , cartesian coordinate system , mathematics , image plane , image (mathematics) , biochemistry , chemistry , geometry , control (management) , gene

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

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