Automatic location of frame deletion point for digital video forensics

Chunhui Feng, Zhengquan Xu, Wenting Zhang, Yanyan Xu
{"title":"Automatic location of frame deletion point for digital video forensics","authors":"Chunhui Feng, Zhengquan Xu, Wenting Zhang, Yanyan Xu","doi":"10.1145/2600918.2600923","DOIUrl":null,"url":null,"abstract":"Detection of frame deletion is of great significance in the field of video forensics. Several approaches have been presented through analyzing the side effect caused by frame deletion. However, most of the current approaches can detect the existence of frame deletion but not the exact location of it. In this paper, we present a method which can directly locate the frame deletion point. Through the analysis of the distinguishing fluctuation feature of motion residual caused by frame deletion compared to interference frames and ordinary video content jitter in tampered video sequence, an algorithm based on the total motion residual of video frame is proposed to detect the frame deletion point. Moreover, an initiative processing procedure for frame motion residual and an adaptive threshold detector are introduced so that the robustness of the detection can be markedly improved. Experimental results show that the proposed algorithm is effective in generalized scenarios such as different encoding settings, rapid or slow motion sequences and multiple group of picture deletion. It also has a high performance that the true positive rate reaches 90% and the false alarm rate is less than 0.8%.","PeriodicalId":243756,"journal":{"name":"Information Hiding and Multimedia Security Workshop","volume":"4 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2014-06-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"34","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Information Hiding and Multimedia Security Workshop","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/2600918.2600923","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 34

Abstract

Detection of frame deletion is of great significance in the field of video forensics. Several approaches have been presented through analyzing the side effect caused by frame deletion. However, most of the current approaches can detect the existence of frame deletion but not the exact location of it. In this paper, we present a method which can directly locate the frame deletion point. Through the analysis of the distinguishing fluctuation feature of motion residual caused by frame deletion compared to interference frames and ordinary video content jitter in tampered video sequence, an algorithm based on the total motion residual of video frame is proposed to detect the frame deletion point. Moreover, an initiative processing procedure for frame motion residual and an adaptive threshold detector are introduced so that the robustness of the detection can be markedly improved. Experimental results show that the proposed algorithm is effective in generalized scenarios such as different encoding settings, rapid or slow motion sequences and multiple group of picture deletion. It also has a high performance that the true positive rate reaches 90% and the false alarm rate is less than 0.8%.
用于数字视频取证的帧删除点自动定位
帧删除检测在视频取证领域具有重要意义。通过分析帧删除的副作用,提出了几种方法。然而,目前的大多数方法可以检测到帧删除的存在,但不能检测到它的确切位置。本文提出了一种直接定位帧删除点的方法。通过分析删帧引起的运动残差与篡改视频序列中干扰帧和普通视频内容抖动的区别波动特征,提出了一种基于视频帧总运动残差的删帧点检测算法。此外,还引入了帧运动残差的主动处理方法和自适应阈值检测器,显著提高了检测的鲁棒性。实验结果表明,该算法在不同编码设置、快慢动作序列和多组图片删除等通用场景下都是有效的。该方法还具有真阳性率达90%,虚警率小于0.8%的高性能。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 求助全文
来源期刊
自引率
0.00%
发文量
0
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:604180095
Book学术官方微信