Conference Paper

Detecting Video Forgeries Based on Noise Characteristics.

DOI: 10.1007/978-3-540-92957-4_27 Conference: Advances in Image and Video Technology, Third Pacific Rim Symposium, PSIVT 2009, Tokyo, Japan, January 13-16, 2009. Proceedings
Source: DBLP

ABSTRACT The recent development of video editing techniques enables us to create realistic synthesized videos. Therefore using video data as evidence in places such as a court of law requires a method to detect forged videos. In this paper we propose an approach to detect suspicious regions in video recorded from a static scene by using noise character- istics. The image signal contains irradiance-dependent noise where the relation between irradiance and noise depends on some parameters; they include inherent parameters of a camera such as quantum efficiency and a response function, and recording parameters such as exposure and elec- tric gain. Forged regions from another video camera taken under different conditions can be differentiated when the noise characteristics of the re- gions are inconsistent with the rest of the video.

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    ABSTRACT: In the digital multimedia era, it is increasingly important to ensure the integrity and authenticity of the vast volumes of video data. A novel approach is proposed for detecting video forgery based on ghost shadow artifact in this paper. Ghost shadow artifact is usually introduced when moving objects are removed by video inpainting. In our approach, ghost shadow artifact is accurately detected by inconsistencies of the moving foreground segmented from the video frames and the moving track obtained from the accumulative frame differences, thus video forgery is exposed. Experiments show that our approach achieves promising results in video forgery detection.

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May 15, 2014