文章基本信息

标题：Robust Video Content Authentication using Video Binary Pattern and Extreme Learning Machine
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作者：Mubbashar Sadddique ; Khurshid Asghar ; Tariq Mehmood 等
期刊名称：International Journal of Advanced Computer Science and Applications(IJACSA)
印刷版ISSN：2158-107X
电子版ISSN：2156-5570
出版年度：2019
卷号：10
期号：8
DOI：10.14569/IJACSA.2019.0100833
出版社：Science and Information Society (SAI)
摘要：Recently, due to easy accessibility of smartphones, digital cameras and other video recording devices, a radical enhancement has been experienced in the field of digital video technology. Digital videos have become very vital in court of law and media (print, electronic and social). On the other hand, a widely-spread availability of Video Editing Tools (VETs) have made video tampering very easy. Detection of this tampering is very important, because it may affect the understanding and interpretation of video contents. Existing techniques used for detection of forgery in video contents can be broadly categorized into active and passive. In this research a passive technique for video tampering detection in spatial domain is proposed. The technique comprises of two phases: 1) Extraction of features with proposed Video Binary Pattern (VBP) descriptor, and 2) Extreme Learning Machine (ELM) based classification. Experimental results on different datasets reveal that the proposed technique achieved accuracy 98.47%.
关键词：Video forgery; spatial video forgery; passive forgery detection; Video Binary Pattern (VBP); feature extraction