摘要
帧复制粘贴是一种常见的时域篡改方式,篡改者采用这种方式来移除视频中某段内容,如犯罪现场、犯罪证据等.针对这种篡改,已经有不少方案被提出,但是它们有两个缺点:一采用固定的阈值;二时间复杂度很高.大部分被篡改视频会经过再压缩处理,由于视频压缩基本是有损压缩,可能会导致固定阈值失去应有作用.因此,本文提出一种基于动态阈值的被动取证算法,来增强算法的鲁棒性,并且通过引入字典排序算法来缩小帧匹配时的搜索范围,成功降低了时间复杂度.文章采用精确度、召回率和平均每帧计算时间来对提出算法的性能进行评估,结果表明本算法在这三方面都优于其他算法,而且具有更好的鲁棒性.
Frame duplication forgery is a very common operation for video tampering in the temporal domain. By removing some frames which contain a crime scene or crime evidence, the forger can change the video content. A lot of solutions have been proposed for detecting this type of tempering operation. However, there are two disadvantages. The first one is fixed threshold; the other is huge computation. In general, frame duplication forgery and re-compression would be performed on a video at the same time. Since re-compression will cause data lost, the fixed thresholds may lose their effects. Therefore, an algorithm based on dynamic threshold is proposed in this paper, which can improve the robustness. Additionally, the proposed method adopts dictionary order algorithm to reduce the search scope of frame matching and the time complexity. Three performance indices： precision, recall and average computation time per frame are employed to evaluate our algorithm. The results demonstrate that the proposed method outperforms the existing methods in terms of precision, recall and computation time.
出处
《计算机系统应用》
2016年第12期108-116,共9页
Computer Systems & Applications
关键词
帧复制粘贴
视频取证
时域篡改
动态阈值
结构相识性系数
frame duplication
digital video forensics
temporal forgery
dynamic threshold
structural similarity index
