Mobile Camera Source Identification with SVD

Soobhany, A.-R.; Lam, K.P.; Fletcher, P.; Collins, D.J.

Abstract

A novel method for extracting the characterising sensor pattern noise (SPN) from digital images is presented. Based on the spectral decomposition technique of Singular Value Decomposition, the method estimates the SPN of each image in terms of its energy level by first transforming the image/signals into a linear additive noise model that separates the photo response non-uniformity (PRNU) of the associated camera from the signal subspace. The camera reference signatures of the individual cameras are computed from a sample of their respective images and compared with a mixture of image signatures from a set of known camera devices. The statistical properties of the method were studied using the Student’s t-test constructed under the null hypothesis formalism. Our studies show that it is possible to determine the source device of digital images from camera phones using such method of signature extraction, with encouraging results.

Citation

Soobhany, A., Lam, K., Fletcher, P., & Collins, D. (2016). Mobile Camera Source Identification with SVD. In Innovations and Advances in Computing, Informatics, Systems Sciences, Networking and Engineering (123-131). https://doi.org/10.1007/978-3-319-06773-5_18

• Conference Name: Innovations and Advances in Computing, Informatics, Systems Sciences, Networking and Engineering
• Acceptance Date: Oct 16, 2014
• Online Publication Date: Nov 7, 2014
• Publication Date: Sep 24, 2016
• Publicly Available Date: May 26, 2023
• Publisher: Springer Verlag
• Pages: 123-131
• Series Title: CISSE 2014
• Book Title: Innovations and Advances in Computing, Informatics, Systems Sciences, Networking and Engineering
• ISBN: 978-3-319-38365-1; 978-3-319-06772-8
• DOI: https://doi.org/10.1007/978-3-319-06773-5_18
• Keywords: source identification, singular value decomposition, digital image forensics, sensor pattern noise, PRNU, mobile camera phone
• Publisher URL: http://dx.doi.org/10.1007/978-3-319-06773-5_18
• Additional Information: Lecture Notes in Electrical Engineering