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%0 Conference Proceedings
%4 sid.inpe.br/sibgrapi/2012/07.12.14.20
%2 sid.inpe.br/sibgrapi/2012/07.12.14.20.52
%T Open Set Source Camera Attribution
%D 2012
%A Costa, Filipe de Oliveira,
%A Eckmann, Michael,
%A Scheirer, Walter J.,
%A Rocha, Anderson,
%@affiliation University of Campinas
%@affiliation Skidmore College
%@affiliation University of Colorado
%@affiliation University of Campinas
%E Freitas, Carla Maria Dal Sasso,
%E Sarkar, Sudeep,
%E Scopigno, Roberto,
%E Silva, Luciano,
%B Conference on Graphics, Patterns and Images, 25 (SIBGRAPI)
%C Ouro Preto
%8 Aug. 22-25, 2012
%S Proceedings
%I IEEE Computer Society
%J Los Alamitos
%K Digital Forensics, Open Set Recognition, Camera Attribution, Sensor Fingerprinting.
%X Similar to ballistic tests in which we match a gun to its bullets, we can identify a given digital camera that acquired an image under investigation. In this paper, we discuss a method for identifying whether or not an image was captured by a specific digital camera. The method relies on noise residual features related to the images under investigation. Our approach considers an "open set" recognition scenario, under which we can not rely on the assumption of full access to all of the potential source cameras. This is the only scenario investigators are faced with in the real world. In this case, we model the decision space to take advantage of a few known cameras and carve the decision boundaries to decrease false matches increasing the reliability of image source attribution as an aid for digital forensics in the court of law. This approach performs favorably vs. the state-of-the-art.
%@language en
%3 sibgrapi-2012-filipe-costa-final.pdf


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