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 this paper, a novel video inter-frame forgery detection scheme based on optical flow consistency is proposed. It is based on the finding that inter-frame forgery will disturb the optical flow consistency. This paper noticed the subtle difference between frame insertion and deletion, and proposed different detection schemes for them. A window based rough detection method and binary searching scheme are proposed to detect frame insertion forgery. Frame-to-frame optical flows and double adaptive thresholds are applied to detect frame deletion forgery. This paper not only detects video forgery, but also identifies the forgery model. Experiments show that our scheme achieves a good performance in identifying frame insertion and deletion model.
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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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    ABSTRACT: Digital forensics is one of the cornerstones to investigate criminal activities such as fraud, computer security breaches or the distribution of illegal content. The importance and relevance of this research fields attracted various research institutes leading to substantial progress in the area of digital investigations. One essential piece of evidence is multimedia data. For this reason this paper provides an overview of the state-of-the-art in the forensic investigation of multimedia data, the relationship between the various research fields and further potential research activities.
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