Fourier-Residual for Printer Identification

Wang, Z; Shivakumara, P; Lu, T; Basavanna, M; Pal, U; Blumenstein, M

Fourier-Residual for Printer Identification

Wang, Z Shivakumara, P Lu, T Basavanna, M Pal, U Blumenstein, M

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Publication Type:: Conference Proceeding
Citation:: Proceedings of the International Conference on Document Analysis and Recognition, ICDAR, 2017, 1 pp. 1114 - 1119
Issue Date:: 2017-07-02

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Field	Value	Language
dc.contributor.author	Wang, Z	en_US
dc.contributor.author	Shivakumara, P	en_US
dc.contributor.author	Lu, T	en_US
dc.contributor.author	Basavanna, M	en_US
dc.contributor.author	Pal, U	en_US
dc.contributor.author	Blumenstein, M https://orcid.org/0000-0002-9908-3744	en_US
dc.date.issued	2017-07-02	en_US
dc.identifier.citation	Proceedings of the International Conference on Document Analysis and Recognition, ICDAR, 2017, 1 pp. 1114 - 1119	en_US
dc.identifier.isbn	9781538635865	en_US
dc.identifier.issn	1520-5363	en_US
dc.identifier.uri	http://hdl.handle.net/10453/133748
dc.description.abstract	© 2017 IEEE. Printer identification is challenging due to advanced software technologies in the field of forgery detection. This paper presents a new idea of using the Fourier transform residual for the identification of documents printed by different printers. The proposed approach first convolves a Laplacian mask with a Fourier transform in the frequency domain to smoothen the edges. Next, we apply an inverse Fourier transform to reconstruct images from smoothed information (RFL). Similarly, the proposed approach reconstructs images using gray information of the input image (RFG). Then the residual is calculated by subtracting RFG from RFL. The set of statistical features, texture and spatial features are extracted from residual images for printer identification. Experimental results with the existing method on our dataset and a standard dataset show that the proposed approach outperforms the existing approach on both the datasets in terms of classification rate, recall, precision and F-measure.	en_US
dc.relation.ispartof	Proceedings of the International Conference on Document Analysis and Recognition, ICDAR	en_US
dc.relation.isbasedon	10.1109/ICDAR.2017.184	en_US
dc.title	Fourier-Residual for Printer Identification	en_US
dc.type	Conference Proceeding
utslib.citation.volume	1	en_US
utslib.for	0801 Artificial Intelligence and Image Processing	en_US
pubs.embargo.period	Not known	en_US
pubs.organisational-group	/University of Technology Sydney
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology
pubs.organisational-group	/University of Technology Sydney/Strength - CAI - Centre for Artificial Intelligence
pubs.organisational-group	/University of Technology Sydney/Strength - QSI - Centre for Quantum Software and Information
utslib.copyright.status	closed_access
pubs.publication-status	Published	en_US
pubs.volume	1	en_US

Abstract:

© 2017 IEEE. Printer identification is challenging due to advanced software technologies in the field of forgery detection. This paper presents a new idea of using the Fourier transform residual for the identification of documents printed by different printers. The proposed approach first convolves a Laplacian mask with a Fourier transform in the frequency domain to smoothen the edges. Next, we apply an inverse Fourier transform to reconstruct images from smoothed information (RFL). Similarly, the proposed approach reconstructs images using gray information of the input image (RFG). Then the residual is calculated by subtracting RFG from RFL. The set of statistical features, texture and spatial features are extracted from residual images for printer identification. Experimental results with the existing method on our dataset and a standard dataset show that the proposed approach outperforms the existing approach on both the datasets in terms of classification rate, recall, precision and F-measure.

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http://hdl.handle.net/10453/133748