摘要
相邻帧间相似性原理的传统视频被动取证方法会对画面运动剧烈的视频发生大量误检测,针对这个问题,提出了一种融合空间约束和梯度结构信息的视频篡改检测方法。首先,利用空间约束准则,提取低运动区域和高纹理区域,并将两个区域进行融合,获取顽健的量化相关性丰富区域用于提取视频最优相似性特征;然后,改进原有特征的提取和描述方法,运用符合人类视觉系统特性的梯度结构相似性GSSIM来计算空间约束相关性值,最后,利用切比雪夫不等式对篡改点进行定位。实验证明,针对画面运动剧烈的视频,所提算法误检率更低,精确度更高。
The traditional video passive forensics method using only the principle of similarity between adjacent frames will cause a lot of false detection for the video with severe motion.Aiming at this problem,a video tamper detection method combining spatial constraints and gradient structure information was proposed.Firstly,the low motion region and the high texture region were extracted by using spatial constraint criteria.The two regions were merged to obtain the robust quantitative correlation rich regions for extracting video optimal similarity features.Then improving the extraction and description methods of the original features,and using the similarity of the gradient structure in accordance with the characteristics of the human visual system to calculate the spatial constraint correlation value.Finally,the tampering points were located by the Chebyshev inequality.Experiments show that the proposed algorithm has lower false detection rate and higher accuracy.
作者
普菡
黄添强
翁彬
肖辉
黄维
PU Han;HUANG Tianqiang;WENG Bin;XIAO Hui;HUANG Wei(Mathematics and Informatics,Fujian Normal University,Fuzhou 350007,China;Fujian Provincial Engineering Research Center of Big Data Analysis and Application,Fuzhou 350007,China;Digital Fujian Big Data Security Technology Institute,Fuzhou 350007,China)
出处
《网络与信息安全学报》
2019年第5期64-79,共16页
Chinese Journal of Network and Information Security
基金
国家重点研发计划专项基金资助项目(No.2018YFC1505805)
应用数学福建省高校重点实验室基金资助项目(No.SX201803)~~
关键词
空间约束
量化相关性丰富区域
梯度结构相似性
画面运动剧烈的视频
spatial constraints
the quantitative correlation rich regions
GSSIM(gradient structure similarity)
videos with severe motion
