arrow
返回

A video forgery detection algorithm based on compressive sensing

delete2014-03-02
delete34
PRE
AI
苏
苏立超 (Lichao Su) *
T
Tianqiang Huang
DOI:10.1007/s11042-014-1915-4delete
delete原文链接
delete原文求助
delete分享
delete收藏
摘要

摘要

En 中文
Video processing software is often used to delete moving objects and modify the forged regions with the information provided by the areas around them. However, few algorithms have been suggested for detecting this form of tampering. In this paper, a novel algorithm based on compressive sensing is proposed for the detection in which the moving foreground was removed from background. Firstly, the features of the difference between frames are obtained through K-SVD (k-Singular Value Decomposition), and then random projection is used to project the features into the lower-dimensional subspace which is clustered by k-means, and finally the detection results are combined to output. The experimental results show that our algorithm has higher detection accuracy and better robustness than that of the previous algorithms.
Keyword:
Video Forgery
K-SVD
Compressive Sensing
Passive Forensics
AI总结

AI总结

对已上传原文的论文进行重点信息的提取,主要内容包括:简要概述、研究摘要、背景介绍、关键亮点、图文解析、展望与总结。

期刊

Multimedia Tools and Applications 封面图
Multimedia Tools and Applications
IF:
3
论文数:
2.0W
被引数:
3.2W

机构

F
Fujian Normal University
学者数:
1.2W
论文数: 8.0K
被引数: 1.3W
引用论文

引用论文

err分享
err收藏
ntLink: A Toolkit for De Novo Genome Assembly Scaffolding and Mapping Using Long Reads
err2023-04-11
err0
errOAAI
errLauren Coombe; René L. Warren; Johnathan Wong; Vladimir Nikolic; Inanc Birol
err分享
err收藏
An introduction to compressive sampling压缩采样简介
err2008-03-01
err8.6K
PREAI
errCandes, Emmanuel J.; Wakin, Michael B.
err分享
err收藏
err分享
err收藏
学者 查看更多内容