The IRMA Community
Newsletters
Research IRM
Click a keyword to search titles using our InfoSci-OnDemand powered search:
|
A Novel Video Forgery Detection Model Based on Triangular Polarity Feature Classification
|
|
Author(s): Chee Cheun Huang (Institute for Infocomm Research, A*STAR, Singapore, Singapore), Chien Eao Lee (Institute for Infocomm Research, A*STAR, Singapore, Singapore)and Vrizlynn L. L. Thing (Institute for Infocomm Research, A*STAR, Singapore, Singapore)
Copyright: 2020
Volume: 12
Issue: 1
Pages: 21
Source title:
International Journal of Digital Crime and Forensics (IJDCF)
Editor(s)-in-Chief: Feng Liu (Chinese Academy of Sciences, China)
DOI: 10.4018/IJDCF.2020010102
Purchase
|
Abstract
Video forgery has been increasing over the years due to the wide accessibility of sophisticated video editing software. A highly accurate and automated video forgery detection system will therefore be vitally important in ensuring the authenticity of forensic video evidences. This article proposes a novel Triangular Polarity Feature Classification (TPFC) video forgery detection framework for video frame insertion and deletion forgeries. The TPFC framework has high precision and recall rates with a simple and threshold-less algorithm designed for real-world applications. System robustness evaluations based on cross validation and different database recording conditions were also performed and validated. Evaluation on the performance of the TPFC framework demonstrated the efficacy of the proposed framework by achieving a recall rate of up to 98.26% and precision rate of up to 95.76%, as well as high localization accuracy on detected forged videos. The TPFC framework is further demonstrated to be capable of outperforming other modern video forgery detection techniques available today.
Related Content
|
Shakir A. Mehdiyev, Tahmasib Kh. Fataliyev.
© 2024.
17 pages.
|
|
Fuhai Jia, Yanru Jia, Jing Li, Zhenghui Liu.
© 2024.
13 pages.
|
|
Dawei Zhang.
© 2024.
16 pages.
|
|
Yuwen Zhu, Lei Yu.
© 2023.
16 pages.
|
|
Vijay Kumar, Sahil Sharma, Chandan Kumar, Aditya Kumar Sahu.
© 2023.
14 pages.
|
|
Wenjun Yao, Ying Jiang, Yang Yang.
© 2023.
20 pages.
|
|
Dawei Zhang.
© 2023.
14 pages.
|
|
|