计算机工程

• 多媒体技术及应用 • 上一篇    下一篇

基于多尺度互信息量的数字视频帧篡改检测

林新棋a,b ,李海涛a,林云玫a   

  1. (福建师范大学a. 数学与计算机科学学院; b. 福建省网络安全与密码技术重点实验室,福州350007)
  • 收稿日期:2014-06-06 出版日期:2015-04-15 发布日期:2015-04-15
  • 作者简介:林新棋(1972 - ),男,副教授、博士,主研方向:多媒体信息处理,编码理论;李海涛、林云玫,硕士研究生。
  • 基金项目:
    福建省教育厅基金资助项目(JA12075,JA10064,JB11036);福建省科技厅高校产学合作科技基金资助重大项目(2012H 6006);福建省高等学校科技创新团队基金资助项目(J1917);福建师范大学校创新团队基金资助项目“网络与信息安全关键理论和技 术”(IRTL1207)。

Detection of Frame Forgery in Digital Video Based on Multi-scale Mutual Information

LIN Xinqi a,b ,LI Haitao a ,LIN Yunmei a   

  1. (a. Department of Mathematics and Computer Science; b. Fujian Provincial Key Laboratory of Network Security and Cryptography,Fujian Normal University,Fuzhou 350007,China)
  • Received:2014-06-06 Online:2015-04-15 Published:2015-04-15

摘要: 针对单镜头视频时域篡改问题,提出一个以内容相似性为基础的视频篡改被动盲检测算法。通过高斯金字塔变换获得视频帧的3 种尺度视觉内容,根据信息论定义相邻两帧的归一化平均互信息,采用线性组合构建多尺度归一化互信息描述子,实现相邻两帧多尺度视觉内容相似性的度量。利用局部离群点检测算法计算视觉内容相似性异常度,使用阈值法检测视频篡改位置。实验结果表明,该算法不仅能有效地检测出视频帧删除、复制以及插入3 种篡改的位置,而且适用于不同编码格式视频间和同源的篡改。在检准度和检全率上优于现有的时域篡改检测算法。

关键词: 视频篡改, 多尺度分析, 互信息量, 相似度, 异常度

Abstract: Aiming at the time tampering problem in the single video shot,a new algorithm based on the content similarity is proposed to detect the tampers of frame duplication,deletion and insertion. Firstly,the three-scale visual contents are obtained by using the Gaussian pyramid transform on every frame. Then,the normalized mutual information is defined on the single scale visual content of adjacent frames based on information theory. And the descriptor of multiscale normalized mutual information is computed by linear combination. Thirdly,the abnormal degree of content similarity is computed by local outlier detection algorithm. Finally,the forgery places are detected by threshold. Experimental results show that the proposed algorithm can effectively localize the tamped position of the frame duplication,insertion,deletion tampers,and can be fit for the forgery of different coding formats and different cameras. The results also show that the proposed algorithm outperforms the existed algorithms in terms of precision and recall.

Key words: video forgery, multi-scale analysi, mutual information, similarity degree, abnormal degree

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