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针对视频运动补偿帧率提升篡改的主动混噪取证算法

李然 梅腊腊 邬长安 朱秀昌

李然, 梅腊腊, 邬长安, 朱秀昌. 针对视频运动补偿帧率提升篡改的主动混噪取证算法[J]. 电子与信息学报, 2018, 40(3): 713-720. doi: 10.11999/JEIT170502
引用本文: 李然, 梅腊腊, 邬长安, 朱秀昌. 针对视频运动补偿帧率提升篡改的主动混噪取证算法[J]. 电子与信息学报, 2018, 40(3): 713-720. doi: 10.11999/JEIT170502
LI Ran, MEI Lala, WU Chang'an, ZHU Xiuchang. Active Noised-mixed Forensics Algorithm for Tampering of Video Motion-compensated Frame Rate Up-conversion[J]. Journal of Electronics & Information Technology, 2018, 40(3): 713-720. doi: 10.11999/JEIT170502
Citation: LI Ran, MEI Lala, WU Chang'an, ZHU Xiuchang. Active Noised-mixed Forensics Algorithm for Tampering of Video Motion-compensated Frame Rate Up-conversion[J]. Journal of Electronics & Information Technology, 2018, 40(3): 713-720. doi: 10.11999/JEIT170502

针对视频运动补偿帧率提升篡改的主动混噪取证算法

doi: 10.11999/JEIT170502
基金项目: 

国家自然科学基金(61501393)

Active Noised-mixed Forensics Algorithm for Tampering of Video Motion-compensated Frame Rate Up-conversion

Funds: 

The National Natural Science Foundation of China (61501393)

  • 摘要: 运动补偿帧率提升(MC-FRUC)是常见的视频时域篡改手段。现有方法依靠被动分析视频统计特征发现MC-FRUC篡改,然而,视频统计特性的非平稳性影响了取证性能的稳定性。该文提出一种主动混噪取证算法,通过预先混入统计特性已知的高斯白噪声,提高MC-FRUC取证的准确度。首先,利用伪随机序列生成高斯白噪声,加入原始视频序列。接着,由小波系数的绝对中位差预测各视频帧中混入高斯噪声的标准差。最后,检测高斯噪声标准差的时域变化周期性,通过硬阈值判决,自动甄别MC-FRUC篡改。实验结果表明,针对不同的MC-FRUC伪造方法,提出算法均表现出良好的取证性能,尤其是当采用去噪、压缩等操作后处理视频后,提出算法仍能确保较高的检测准确度。
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出版历程
  • 收稿日期:  2017-05-24
  • 修回日期:  2017-11-10
  • 刊出日期:  2018-03-19

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