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Digital Image Forgery Detection by Local Statistical Models
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SYSNO ASEP 0348592 Document Type C - Proceedings Paper (int. conf.) R&D Document Type Conference Paper Title Digital Image Forgery Detection by Local Statistical Models Author(s) Grim, Jiří (UTIA-B) RID, ORCID
Somol, Petr (UTIA-B) RID
Pudil, Pavel (UTIA-B) RIDNumber of authors 3 Source Title 2010 Sixth International Conference on Intelligent Information Hiding and Multimedia Signal Processing. - Los Alamitos, California : IEEE computer society, 2010 / Echizen Isao ; Pan Jeng-Shyang ; Fellner Dieter ; Nouak Alexander ; Kuijper Arjan ; Jain Lakhmi C. - ISBN 978-0-7695-4222-5 Pages s. 579-582 Number of pages 4 s. Action 6th International Conference on Intelligent Information Hiding and Multimedia Signal Processing (IIH-MSP 2010) Event date 15.10.2010-17.10.2010 VEvent location Darmstadt Country DE - Germany Event type WRD Language eng - English Country US - United States Keywords forgery detection ; local statistical models ; distribution mixtures ; EM algorithm Subject RIV IN - Informatics, Computer Science R&D Projects 1M0572 GA MŠMT - Ministry of Education, Youth and Sports (MEYS) GA102/08/0593 GA ČR - Czech Science Foundation (CSF) GA102/07/1594 GA ČR - Czech Science Foundation (CSF) CEZ AV0Z10750506 - UTIA-B (2005-2011) DOI 10.1109/IIHMSP.2010.147 Annotation We propose an application of local statistical models in the form of a locally estimated Gaussian mixture to image forgery detection. The estimated mixture is used to compute the so called log-likelihood transformation of the original image. We show that image manipulations of different type may be visible in a suitably designed log-likelihood image. Unlike other methods the forgery detection based on local statistical model is rather non-specific and suitable to emphasize various traces of possible image tampering without any prior information. Workplace Institute of Information Theory and Automation Contact Markéta Votavová, votavova@utia.cas.cz, Tel.: 266 052 201. Year of Publishing 2011
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