scholarly journals Digital Video Source Identification Based on Green-Channel Photo Response Non-Uniformity (G-PRNU)

2016 ◽  
Author(s):  
Al-Athamneh M ◽  
Kurugollu F ◽  
Crookes D ◽  
Farid M
Keyword(s):  
Source Identification ◽  
Digital Video ◽  
Green Channel ◽  
Video Source ◽  
Photo Response

scholarly journals Digital Video Source Identification Using Sensor Pattern Noise with Morphology Filtering

2017 ◽  
Vol 6 (1) ◽  
pp. 15-22 ◽  
Author(s):  
Sang-Hyeong Lee ◽  
Dong-Hyun Kim ◽  
Tae-Woo Oh ◽  
Ki-Bom Kim ◽  
Hae-Yeoun Lee
Keyword(s):  
Source Identification ◽  
Digital Video ◽  
Video Source ◽  
Pattern Noise ◽  
Sensor Pattern Noise

scholarly journals Digital Video Source Identification Based on Container’s Structure Analysis

IEEE Access ◽  
2020 ◽  
Vol 8 ◽  
pp. 36363-36375
Author(s):  
Raquel Ramos Lopez ◽  
Elena Almaraz Luengo ◽  
Ana Lucila Sandoval Orozco ◽  
Luis Javier Garcia Villalba
Keyword(s):  
Structure Analysis ◽  
Source Identification ◽  
Digital Video ◽  
Video Source

scholarly journals Hybrid reference-based Video Source Identification

Sensors ◽  
2019 ◽  
Vol 19 (3) ◽  
pp. 649 ◽  
Author(s):  
Massimo Iuliani ◽  
Marco Fontani ◽  
Dasara Shullani ◽  
Alessandro Piva
Keyword(s):  
Social Media ◽  
Source Identification ◽  
State Of The Art ◽  
Visual Media ◽  
Multimedia Forensics ◽  
Reference Pattern ◽  
Still Images ◽  
Video Source ◽  
Video Frames ◽  
Social Media Platforms

Millions of users share images and videos generated by mobile devices with different profiles on social media platforms. When publishing illegal content, they prefer to use anonymous profiles. Multimedia Forensics allows us to determine whether videos or images have been captured with the same device, and thus, possibly, by the same person. Currently, the most promising technology to achieve this task exploits unique traces left by the camera sensor into the visual content. However, image and video source identification are still treated separately from one another. This approach is limited and anachronistic, if we consider that most of the visual media are today acquired using smartphones that capture both images and videos. In this paper we overcome this limitation by exploring a new approach that synergistically exploits images and videos to study the device from which they both come. Indeed, we prove it is possible to identify the source of a digital video by exploiting a reference sensor pattern noise generated from still images taken by the same device. The proposed method provides performance comparable with or even better than the state-of-the-art, where a reference pattern is estimated from video frames. Finally, we show that this strategy is effective even in the case of in-camera digitally stabilized videos, where a non-stabilized reference is not available, thus solving the limitations of the current state-of-the-art. We also show how this approach allows us to link social media profiles containing images and videos captured by the same sensor.

Video source identification in lossy wireless networks

2013 ◽  
Author(s):  
Shaxun Chen ◽  
Amit Pande ◽  
Kai Zeng ◽  
Prasant Mohapatra
Keyword(s):  
Wireless Networks ◽  
Source Identification ◽  
Video Source

Video source identification from MP4 data based on field values in atom/box attributes

2021 ◽  
Keyword(s):  
International Symposium ◽  
Source Identification ◽  
Fast Track ◽  
Video Source ◽  
Electronic Imaging

Fast track article for IS&T International Symposium on Electronic Imaging 2021: Media Watermarking, Security, and Forensics 2021 proceedings.

Dealing with video source identification in social networks

2017 ◽  
Vol 57 ◽  
pp. 1-7 ◽  
Author(s):  
Irene Amerini ◽  
Roberto Caldelli ◽  
Andrea Del Mastio ◽  
Andrea Di Fuccia ◽  
Cristiano Molinari ◽  
...  
Keyword(s):  
Social Networks ◽  
Source Identification ◽  
Video Source

scholarly journals Digital Video Source Acquisition Forgery Technique Based on Pattern Sensor Noise Extraction

IEEE Access ◽  
2019 ◽  
Vol 7 ◽  
pp. 157363-157373 ◽  
Author(s):  
Ana Lucila Sandoval Orozco ◽  
Carlos Quinto Huaman ◽  
Jenny Alexandra Cifuentes Quintero ◽  
Luis Javier Garcia Villalba
Keyword(s):  
Digital Video ◽  
Sensor Noise ◽  
Video Source

scholarly journals Video Source Identification Algorithm Based on 3D Geometric Transformation

2020 ◽  
Vol 35 (6) ◽  
pp. 513-521
Author(s):  
Jian Li ◽  
Yang Lv ◽  
Bin Ma ◽  
Meihong Yang ◽  
Chunpeng Wang ◽  
...  
Keyword(s):  
Source Identification ◽  
Geometric Transformation ◽  
Identification Algorithm ◽  
Video Source

Ultrafast photo-response in (EDO)2PF6

2004 ◽  
Vol 114 ◽  
pp. 143-145 ◽  
Author(s):  
Naoki Uchida ◽  
Shin-ya Koshihara ◽  
Tadahiko Ishikawa ◽  
Akira Ota ◽  
Souichi Fukaya ◽  
...  
Keyword(s):  
Photo Response
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