Mohammad Javad Tanakian - Communication, M.Sc, Faculty of Electrical & Computer Engineering, University of Sistan and Baluchestan
Mehdi Rezaei - Signal Processing, Assistant Professor, Faculty of Electrical & Computer Engineering, University of Sistan and Baluchestan
Farahnaz Mohanna - Image Processing, Assistant Professor, Faculty of Electrical & Computer Engineering, University of Sistan and Baluchestan

Digital video stabilization (DVS) allows acquiring video sequences without disturbing jerkiness, removing unwanted camera movements. A good DVS should remove the unwanted camera movements while maintains the intentional camera movements. In this article, we propose a novel DVS algorithm that compensates the camera jitters applying an adaptive fuzzy filter on the global motion of video frames. The adaptive fuzzy filter is a Kalman filter which is tuned by a fuzzy system adaptively to the camera motion characteristics. The fuzzy system is also tuned during operation according to the amount of camera jitters. The fuzzy system uses two inputs which are quantitative representations of the unwanted and the intentional camera movements. Since motion estimation is a computation intensive operation, the global motion of video frames is estimated based on the block motion vectors which resulted by video encoder during motion estimation operation. Furthermore, the proposed method also utilizes an adaptive criterion for filtering and validation of motion vectors. Experimental results indicate a good performance for the proposed algorithm

Adaptive, Digital Video Stabilization, Fuzzy Filter, Kalman Filter, Motion Estimation, Motion Vector, Video Coding