UM
Dense moment feature index and best match algorithms for video copy-move forgery detection
Zhong,Jun Liu1,2; Pun,Chi Man2; Gan,Yan Fen2,3
2020-10-01
Source PublicationInformation Sciences
ISSN0020-0255
Volume537Pages:184-202
AbstractThis paper proposes a video copy-move forgery detection method to effectively address inter/intra-frame forgeries both at the frame and pixel level. First, a unified moment framework is proposed to extract multi-dimensional dense moment features from the video effectively. Second, a novel feature representation method takes each feature sub-map index to represent its every dimensional feature and then concatenates to a 9-digit dense moment feature index. Third, an inter-frame best match algorithm is proposed to search the 9-digit dense moment feature index of each pixel to find its best matches. All the best matches construct the best match map. Fourth, an inter-frame post-processing algorithm identifies the inter-frame forgery video in the best match map firstly and then indicates the corresponding inter-frame forgery regions. Otherwise, the intra-frame post-processing algorithm re-searches the best match of every pixel in each independent frame and then indicates the intra-frame forgery regions. If the video does not belong to the intra-frame forgeries, the video is determined as a genuine one. The experimental results show that the proposed method is effective at addressing the forensics of the genuine/forgery video and locating the inter/intra-frame copy-move forgeries both at the frame and pixel level.
KeywordA 9-digit dense moment feature index A unified moment framework Best match algorithm Video copy-move forgery detection
DOI10.1016/j.ins.2020.05.134
URLView the original
Language英语
Scopus ID2-s2.0-85086385692
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Cited Times [WOS]:1   [WOS Record]     [Related Records in WOS]
Document TypeJournal article
CollectionUniversity of Macau
Affiliation1.GuangDong Mechanical & Electrical College,Guangzhou,China
2.Department of Computer and Information Science,University of Macau,Macau SAR,China
3.South China Business College Guangdong University of Foreign Studies,China
First Author AffilicationUniversity of Macau
Recommended Citation
GB/T 7714
Zhong,Jun Liu,Pun,Chi Man,Gan,Yan Fen. Dense moment feature index and best match algorithms for video copy-move forgery detection[J]. Information Sciences,2020,537:184-202.
APA Zhong,Jun Liu,Pun,Chi Man,&Gan,Yan Fen.(2020).Dense moment feature index and best match algorithms for video copy-move forgery detection.Information Sciences,537,184-202.
MLA Zhong,Jun Liu,et al."Dense moment feature index and best match algorithms for video copy-move forgery detection".Information Sciences 537(2020):184-202.
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