Sep 13, 2010 · In this study, we developed an approach to detect suspicious regions in a video of a static scene on the basis of the noise characteristics. The ...

In this study, we developed an approach to detect suspicious regions in a video of a static scene on the basis of the noise characteristics.

An approach to detect suspicious regions in a video of a static scene on the basis of the noise characteristics, which enables us to highly accurately ...

In this study, we developed an approach to detect suspicious regions in a video of a static scene on the basis of the noise characteristics. The image signal ...

In this study, we developed an approach to detect suspicious regions in a video of a static scene on the basis of the noise characteristics. The image signal ...

Detecting Forgery From Static-Scene Video Based on Inconsistency in Noise Level Functions. Michihiro Kobayashi, Takahiro Okabe, Yoichi Sato. January, 2010.

Fingerprint. Dive into the research topics of 'Detecting forgery from static-scene video based on inconsistency in noise level functions'.

This paper proposes an anti-forensic forged video detection method based on a noise transfer matrix analysis. The primary contributions of the proposed method ...

This paper proposes an approach to detect suspicious regions in video recorded from a static scene by using noise characteristics, where the image signal ...

The basic idea of our proposed method is to use noise inconsistencies between the original video and superimposed segments to detect forgeries. We exploit the.