Visual Computing and Machine Learning Techniques for Digital Forensics
AbstractIt is impressive how fast science has improved day by day in so many different fields. In special, technology advances are shocking so many people bringing to their reality facts that previously were beyond their imagination. Inspired by methods earlier presented in scientific fiction shows, the computer science community has created a new research area named Digital Forensics, which aims at developing and deploying methods for fighting against digital crimes such as digital image forgery.This work presents some of the main concepts associated with Digital Forensics and, complementarily, presents some recent and powerful techniques relying on Computer Graphics, Image Processing, Computer Vision and Machine Learning concepts for detecting forgeries in photographs. Some topics addressed in this work include: source
attribution, spoofing detection, pornography detection, multimedia phylogeny, and forgery detection. Finally, this work highlights the challenges and open problems in Digital Image Forensics to provide the readers with the myriad opportunities available for research.
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How to Cite
Carvalho, T. J. de, Pedrini, H., & Rocha, A. de R. (2015). Visual Computing and Machine Learning Techniques for Digital Forensics. Revista De Informática Teórica E Aplicada, 22(1), 128–153. https://doi.org/10.22456/2175-2745.49492
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