Abstract
Video forensics becomes more and more important than ever before. In this paper a new methodology based on Block-wise Brightness Variance Descriptor (BBVD) is proposed. It is capable of fast detecting video inter-frame forgery. Our proposed algorithm has been tested on a database consisting of 240 original and forged videos. The experiments have demonstrated that the precision rate is about 94.09 % in detecting the insertion forgery and the precision rate is 79.45 % in the forgery localization. Moreover, the time utilized for forgery detecting is shorter than the time used for video replay. On average the time of forgery detection is only about 73.4 % in video replay.
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Acknowledgements
This work was supported by the Project of International Cooperation and Exchanges by Shanghai Committee of Science and Technology (No. 12510708500). And it is also partially supported by the National Natural Science Foundation of China (No. 61272249, 61272439), the Specialized Research Fund for the Doctoral Program of Higher Education (No. 20120073110053).
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Zheng, L., Sun, T., Shi, YQ. (2015). Inter-frame Video Forgery Detection Based on Block-Wise Brightness Variance Descriptor. In: Shi, YQ., Kim, H., Pérez-González, F., Yang, CN. (eds) Digital-Forensics and Watermarking. IWDW 2014. Lecture Notes in Computer Science(), vol 9023. Springer, Cham. https://doi.org/10.1007/978-3-319-19321-2_2
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DOI: https://doi.org/10.1007/978-3-319-19321-2_2
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