The identification of the camera that has acquired a specific image can be performed via several device-related footprints. Among these, it is possible to look for the traces left by the adopted color demosaicing strategy, which varies according to the camera model and vendor. The paper presents an identification strategy that re-processes the analyzed image with a set of distinctive CFA interpolation algorithms (eigenalgorithms) and, according to the correlation of the output with the original image, builds a set of features that permits identifying the algorithm. The proposed solution performs well with respect to other state-of-the-art solutions also when the analyzed image is severely compressed.

Demosaicing strategy identification via eigenalgorithms

BESTAGINI, PAOLO;TAGLIASACCHI, MARCO;TUBARO, STEFANO
2014

Abstract

The identification of the camera that has acquired a specific image can be performed via several device-related footprints. Among these, it is possible to look for the traces left by the adopted color demosaicing strategy, which varies according to the camera model and vendor. The paper presents an identification strategy that re-processes the analyzed image with a set of distinctive CFA interpolation algorithms (eigenalgorithms) and, according to the correlation of the output with the original image, builds a set of features that permits identifying the algorithm. The proposed solution performs well with respect to other state-of-the-art solutions also when the analyzed image is severely compressed.
Proceedings IEEE International Conference on Acoustics, Speech and Signal Processing 2014 (ICASSP-2014)
978-1-4799-2893-4
demosaicing identification, CFA interpolation, Bayer mask, device identification, image forensics
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Utilizza questo identificativo per citare o creare un link a questo documento: http://hdl.handle.net/11311/961652
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