Inter-frame Forgery Detection for Static-Background Video Based on MVP Consistency
作者： Zhenzhen Zhang , Jianjun Hou , Zhaohong Li , Dongdong Li
DOI: 10.1007/978-3-319-31960-5_9
关键词: Point (geometry) 、 Computer security 、 Computer science 、 Motion vector 、 Inter frame 、 Feature extraction 、 Frame (networking) 、 Discontinuity (linguistics) 、 Grayscale 、 Artificial intelligence 、 Pyramid (image processing) 、 Computer vision
摘要: Frame deletion and duplication are common inter-frame tampering methods in digital videos. In this paper, an efficient forensic method based on motion vector pyramid (MVP) its variation factor (VF) is proposed to detect frame videos with static background. This composed of two parts: feature extraction discontinuity point detection. the stage extraction, each video transformed grayscale image firstly. Then, sequence corresponding calculated for every adjacent frames. detection, forgery type identified localized by performing modified generalized ESD test. Experimental results show that at identification localization. Compared other existing our more generic.
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