Source video camera identification for multiply compressed videos originating from YouTube

Authors:
Wiger Van Houten;Zeno Geradts
Affiliations:
Digital Technology and Biometrics department, Netherlands Forensic Institute, Laan van Ypenburg 6 2497 GB The Hague, The Netherlands;Digital Technology and Biometrics department, Netherlands Forensic Institute, Laan van Ypenburg 6 2497 GB The Hague, The Netherlands
Venue:
Digital Investigation: The International Journal of Digital Forensics & Incident Response
Year:
2009

Citing 8
Cited 1

A Non-Local Algorithm for Image Denoising

CVPR '05 Proceedings of the 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05) - Volume 2 - Volume 02
Spatially adaptive statistical modeling of wavelet image coefficients and its application to denoising

ICASSP '99 Proceedings of the Acoustics, Speech, and Signal Processing, 1999. on 1999 IEEE International Conference - Volume 06
Can we trust digital image forensics?

Proceedings of the 15th international conference on Multimedia
Source Camera Identification for Low Resolution Heavily Compressed Images

ICCSA '08 Proceedings of the 2008 International Conference on Computational Sciences and Its Applications
Digital camera identification from sensor pattern noise

IEEE Transactions on Information Forensics and Security
Determining Image Origin and Integrity Using Sensor Noise

IEEE Transactions on Information Forensics and Security
Spatially adaptive wavelet thresholding with context modeling for image denoising

IEEE Transactions on Image Processing
Adaptive wavelet thresholding for image denoising and compression

IEEE Transactions on Image Processing

Verification of video source camera competition (CAMCOM 2010)

ICPR'10 Proceedings of the 20th International conference on Recognizing patterns in signals, speech, images, and videos

Quantified Score

Hi-index	0.00

Visualization

Abstract

The Photo Response Non-Uniformity is a unique sensor noise pattern that is present in each image or video acquired with a digital camera. In this work a wavelet-based technique used to extract these patterns from digital images is applied to compressed low resolution videos originating mainly from webcams. After recording these videos with a variety of codec and resolution settings, the videos were uploaded to YouTube, a popular internet video sharing website. By comparing the average pattern extracted from these resulting downloaded videos with the average pattern obtained from multiple reference cameras of the same brand and type, it was attempted to identify the source camera. This may be of interest in cases of child abuse or child pornography. Depending on the codec, quality settings and recording resolution, very satisfactory results were obtained.