Inter-frame Video Forgery Detection Based on Block-Wise Brightness Variance Descriptor

نویسندگان

  • Lu Zheng
  • Tanfeng Sun
  • Yun Q. Shi
چکیده

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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تاریخ انتشار 2014