Video tampering detection algorithm based on spatial constraint and gradient structure information

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 w...

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Bibliographic Details
Main Authors: Han PU, Tianqiang HUANG, Bin WENG, Hui XIAO, Wei HUANG
Format: Article
Language:English
Published: POSTS&TELECOM PRESS Co., LTD 2019-10-01
Series:网络与信息安全学报
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Online Access:http://www.cjnis.com.cn/thesisDetails#10.11959/j.issn.2096-109x.2019052
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Summary: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.
ISSN:2096-109X