Abstract
Source Camera identification of digital images can be performed by matching the sensor pattern noise (SPN) of the images with that of the camera reference signature. This paper presents a non-decimated wavelet based source camera identification method for digital images. The proposed algorithm applies a non-decimated wavelet transform on the input image and split the image into its wavelet sub-bands. The coefficients within the resulting wavelet high frequency sub-bands are filtered to extract the SPN of the image. Cross correlation of the image SPN and the camera reference SPN signature is then used to identify the most likely source device of the image. Experimental results were generated using images of ten cameras to identify the source camera of the images. Results show that the proposed technique generates superior results to that of the state of the art wavelet based source camera identification.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Soobhany, A.R., Leary, R., Lam, K.P.: On the performance of Li’s unsupervised image classifier and the optimal cropping position of images for Forensic Investigations. Int. J. Digital Crime Forensics (IJDCF) 3, 1–13 (2011)
Gloe, T., Kirchner, M., Winkler, A., Böhme, R.: Can we trust digital image forensics? In: Proceedings of the 15th International Conference on Multimedia, Augsburg, Germany, pp. 78–86 (2007)
Lukas, J., Fridrich, J., Goljan, M.: Digital camera identification from sensor pattern noise. IEEE Trans. Inf. Forensics Secur. 1, 205–214 (2006)
Fridrich, J.: Digital image forensic using sensor noise. IEEE Signal Process. Mag. 26, 26–37 (2009)
Chen, M., Fridrich, J., Goljan, M., Lukas, J.: Determining image origin and integrity using sensor noise. IEEE Trans. Inf. Forensics Secur. 3(1), 74–90 (2008)
Li, C.-T.: Source camera identification using enhanced sensor pattern noise. IEEE Trans. Inf. Forensics Secur. 5, 280–287 (2010)
Alles, E.J., Geradts, Z., Veenman, C.J.: Source camera identification for low resolution heavily compressed images. In: International Conference on Computational Sciences and its Applications, (ICCSA), pp. 557–567 (2008)
Gisolf, F., Malgoezar, A., Baar, T., Geradts, Z.: Improving source camera identification using a simplified total variation based noise removal algorithm. Digital Investig. 10(3), 207–214 (2013)
Soobhany, A.R., Lam, K.P., Fletcher P., Collins, D.: Source identification of camera phones using SVD. In: IEEE International Conference on Image Processing, Melbourne, VIC, pp. 4497–4501 (2013)
Kang, X., Chen, J., Lin, K., Anjie, P.: A context-adaptive SPN predictor for trustworthy source camera identification. EURASIP J. Image Video Process. 2014(1), 1–11 (2014)
Akbari, A.S., Zadeh, P.B., Behringer, R.: Iris segmentation using a non-decimated wavelet transform. In: Proceedings of the 2nd IET International Conference on Intelligent Signal Processing. Savoy Place, London (2015)
Lin, X., Li, C.-T.: Enhancing sensor pattern noise via filtering distortion removal. IEEE Signal Process. Lett. 23(3), 381–385 (2016)
Goljan, M., Fridrich, J., Filler, T.: Large scale test of sensor fingerprint camera identification. In: Proceedings of SPIE Electronic Imaging, Media Forensics and Security XI, vol. 7254, pp. 0I-01–0I-12 (2009)
MATLAB implementation of digital camera fingerprint extraction. http://dde.binghamton.edu/download/camerafingerprint/
Gloe, T., Böhme, R.: The ‘dresden image database’ for benchmarking digital image forensics. In: Proceedings of the 25th Symposium on Applied Computing (ACM SAC), vol. 2, pp. 1585–1591 (2010)
Acknowledgements
This work, as part of the CARI project, is supported by the Police Knowledge Fund, which is administered by the College of Policing, the Home Office, and the Higher Education Funding Council for England (HEFCE). Special thanks to Sofia Soobhany for her insightful comments on the paper.
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2016 Springer International Publishing AG
About this paper
Cite this paper
Soobhany, A.R., Sheikh-Akbari, A., Schreuders, Z.C. (2016). Source Camera Identification Using Non-decimated Wavelet Transform. In: Jahankhani, H., et al. Global Security, Safety and Sustainability - The Security Challenges of the Connected World. ICGS3 2017. Communications in Computer and Information Science, vol 630. Springer, Cham. https://doi.org/10.1007/978-3-319-51064-4_11
Download citation
DOI: https://doi.org/10.1007/978-3-319-51064-4_11
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-51063-7
Online ISBN: 978-3-319-51064-4
eBook Packages: Computer ScienceComputer Science (R0)