Abstract
In this paper we deal with the issue of digital camera identification (DCI) based on images. This area matches the digital forensics (DF) research. This topic has attracted many researchers and number of algorithms for DCI have been proposed. However, majority of them focus only on camera identification with high accuracy without taking into account the speed of image processing. In this paper we propose an effective algorithm for much faster camera identification than state-of-the-art algorithms. Experimental evaluation conducted on two large image datasets including almost 14.000 images confirms that the proposed algorithm achieves high classification accuracy of 97 [%] in much shorter time compared with state-of-the-art algorithms which obtained 92.0 − 96.0 [%]. We also perform a statistical analysis of obtained results which confirms their reliability.
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Acknowledgements
The authors would like to thank the Editorial Office of Optyczne.plFootnote 2 website for sharing part of images utilized in Dataset I.
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This research did not receive any specific grant from funding agencies in the public, commercial, or not-for-profit sectors.
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Appendix:
Appendix:
Due to a large number of confusion matrices, we present them in this Section.
1.1 Experiment I
Results for the brand recognition of Experiment I are presented as Tables 20, 21 and 22 (for Dataset I) and Tables 23, 24 and 25 (for Dataset II—Dresden Image Database).
1.2 Experiment II
Results for the brand recognition of Experiment I are presented as Tables 26, 27, 28, 29, 30 and 31 (for Dataset I) and Tables 32, 33, 34, 35, 36 and 37 (for Dataset II—Dresden Image Database).
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Bernacki, J. Digital camera identification by fingerprint’s compact representation. Multimed Tools Appl 81, 21641–21674 (2022). https://doi.org/10.1007/s11042-022-12468-0
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DOI: https://doi.org/10.1007/s11042-022-12468-0