A System Based on Intrinsic Features for Fraudulent Document Detection
Authors:
- Romain BertrandRBRomain Bertrand
- Petra Gomez-KramerPGPetra Gomez-Kramer
- Oriol Ramos TerradesOTOriol Ramos Terrades
- Patrick FrancoPFPatrick Franco
- Jean-Marc OgierJOJean-Marc Ogier
- 1 August 2013
- conference paper
- Published by Institute of Electrical and Electronics Engineers (IEEE)
- No. 15205363,p. 106-110
Abstract
Paper documents still represent a large amount of information supports used nowadays and may contain critical data. Even though official documents are secured with techniques such as printed patterns or artwork, paper documents suffer from a lack of security. However, the high availability of cheap scanning and printing hardware allows non-experts to easily create fake documents. As the use of a watermarking system added during the document production step is hardly possible, solutions have to be proposed to distinguish a genuine document from a forged one. In this paper, we present an automatic forgery detection method based on document's intrinsic features at character level. This method is based on the one hand on outlier character detection in a discriminant feature space and on the other hand on the detection of strictly similar characters. Therefore, a feature set is computed for all characters. Then, based on a distance between characters of the same class, the character is classified as a genuine one or a fake one.Keywords
This publication has 9 references indexed in Scilit:
- An Evaluation of Popular Copy-Move Forgery Detection ApproachesIEEE Transactions on Information Forensics and Security, 2012
- Distortion Measurement for Automatic Document Verification2011
- Document inspection using text-line alignment2010
- Using DCT Features for Printing Technique and Copy Detection2009
- Automatic Line Orientation Measurement for Questioned Document ExaminationLecture Notes in Computer Science, 2009
- Printing Technique Classification for Document Counterfeit Detection2006
- Global and local document degradation models2002
- Paper based document security - a review1997
- Visual pattern recognition by moment invariantsIRE Transactions on Information Theory, 1962