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Today, many people in the world without any (or with little) knowledge about video recording, thanks to the widespread use of mobile devices (personal digital assistants, mobile phones, etc.), take videos. However, the unwanted movements of their hands typically blur and introduce disturbing jerkiness in the recorded sequences. Many video stabilization techniques have been hence developed with different performances but only fast strategies can be implemented on embedded devices. A fundamental issue is the overall robustness with respect to different scene contents (indoor, outdoor, etc.) and conditions (illumination changes, moving objects, etc.). In this paper, we propose a fast and robust image alignment algorithm for video stabilization purposes. Our contribution is twofold: a fast and accurate block-based local motion estimator together with a robust alignment algorithm based on voting. Experimental results confirm the effectiveness of both local and global motion estimators.