Visual Computing and Machine Learning Techniques for Digital Forensics


  • Tiago Jose de Carvalho University of Campinas
  • Helio Pedrini University of Campinas
  • Anderson de Rezende Rocha University of Campinas



It 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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Author Biography

Tiago Jose de Carvalho, University of Campinas

É funcionário efetivo alocado como Técnico em Tecnologia da Informação no Instituto Federal Sudeste de Minas Gerais (IFSEMG) desde 2004. É graduado em Ciência da Computação pela Universidade Federal de Juiz de Fora (UFJF), mestre e doutor em Ciência da Computação pela Universidade Estadual de Campinas(UNICAMP). Durante seu doutorado investigou problemas na área de análise forense de documentos digitais. Entre seus interesses de pesquisa destacam-se as áreas de computação forense, visão computacional, processamento de imagens e inteligência artificial.




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.



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