Agradecimentos: We thank the financial support of CNPq (Grants #477662/2013-7, and #304352/2012-8), FAPESP (Grant #2010/05647-4), the CAPES DeepEyes project, and Microsoft Research. In addition, we also thank to Dr. Elizabeth S. Chen and Federal University of S ao Paulo, who kindly assisted us with the microscope analysis of the printed letters Ver menos

Abstract: With a huge amount of printed documents nowadays, identifying their source is useful for criminal investigations and also to authenticate digital copies of a document. In this paper, we propose novel techniques for laser printer attribution. Our solutions do not need very high resolution scanning of the investigated document and explore the multidirectional, multiscale and low-level gradient texture patterns yielded by printing devices. The main contributions of this work are: (1) the description of printed areas using multidirectional and multiscale co-occurring texture patterns; (2) description of texture on low-level gradient areas by a convolution texture gradient filter that emphasizes textures in specific transition areas and (3) the analysis of printer patterns in segments of interest, which we call frames, instead of whole documents or only printed letters. We show by experiments in a well documented dataset that the proposed methods outperform techniques described in the literature and present near-perfect classification accuracy being very promising for deployment in real-world forensic investigations Ver menos