Multi-directional and multi-scale perturbation approaches for blind forensic median filtering detection

Issue title: Intelligent Computing for Pattern Recognition, Image Processing and Computer Vision Papers from CIARP 2014, November 2-5, 2014, Puerto Vallarta, Jalisco, Mexico

Guest editors: Eduardo Bayro-Corrochano

Article type: Research Article

Authors: Ferreira, Anselmo^{a; *} | Dos Santos, Jefersson A.^b | Rocha, Anderson^a

Affiliations: [a] Institute of Computing, University of Campinas, São Paulo, Brazil | [b] Department of Computer Science, Universidade Federal de Minas Gerais, Belo Horizonte-MG, Brazil

Correspondence: [*] Corresponding author: Anselmo Ferreira, Institute of Computing, University of Campinas (Unicamp), Av. Albert Einstein, 1251, CEP 13083-852, Campinas, São Paulo, Brazil. E-mail:[email protected]

Abstract: The forensic detection of median filtering has recently attracted the attention of the research community, mainly because of the median filtering potential uses for tampering and concealing image tampering traces in digital images. In this paper, we propose multi-scale and multi-perturbation solutions that build a highly discriminative feature space, which highlights the artifacts of median filtering by means of image quality measures. The proposed methods achieve promising results when validated with a series of real-world test cases, comprising different image compression levels, resolutions, and also a cross-dataset validation protocol.

Keywords: Digital image forensics, median filtering detection, multiple-perturbations, multiple scales

DOI: 10.3233/IDA-160843

Journal: Intelligent Data Analysis, vol. 20, no. s1, pp. S17-S36, 2016