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This paper proposes a framework for video content copy detection for copyright or online video sharing. It utilizes a well-known ordinal measure and incorporates with a hierarchical bitmap indexing structure. This work improves on our previous work by introducing a few features: a new matching algorithm, black border removal, and selecting a suitable number of blocks. With these new features, the system has shown improvements by reducing the computational time and memory space in video matching process. The proposed system is able to handle several of video transformations including change in color, brightness, resolution, contrast, gamma, as well as the addition of noise, blurred, logo or text caption, flip (this case was failed to detect by our previous system). Moreover, by removing black borders before generating the signatures, the system yields better results in cases of ratio (letter/pillar box), zoom in and little crop/shift.
Date of Conference: 13-16 Dec. 2011