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2015 | OriginalPaper | Chapter

Lessons Learned from Automatic Forgery Detection in over 100,000 Invoices

Authors : Joost van Beusekom, Armin Stahl, Faisal Shafait

Published in: Computational Forensics

Publisher: Springer International Publishing

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Abstract

Digitization and automatic processing of incoming paper mail is a crucial component of document management systems and is widely adopted in medium and large enterprises. Besides several advantages of this automated processing, it complicates the first line inspection of incoming documents which are often of vital financial or legal relevance. We have developed a number of different techniques to allow automatic detection of forged or manipulated documents over the last years. In this paper, we present an analysis of the application of our methods on a large real-world dataset of invoices to identify the weaknesses of our existing methods and propose some promising directions of future work in the field.

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previous chapter Stamp Verification for Automated Document Authentication
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Literature
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Hails, J.: Criminal Evidence. p. 150, Thomson Learning, Boston (2004)
2.
van Beusekom, J., Shafait, F., Breuel, T.: Automatic line orientation measurement for questioned document examination. In: Geradts, Z.J.M.H., Franke, K.Y., Veenman, C.J. (eds.) IWCF 2009. LNCS, vol. 5718, pp. 165–173. Springer, Heidelberg (2009) CrossRef
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van Beusekom, J., Shafait, F., Breuel, T.M.: Text-line examination for document forgery detection. Int. J. Doc. Anal. Recogn. 16(2), 189–207 (2013)CrossRef
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van Beusekom, J., Shafait, F., Breuel, T.M.: Combined orientation and skew detection using geometric text-line modeling. Int. J. Doc. Anal. Recogn. 13(2), 79–92 (2010)CrossRef
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Ahmed, A., Shafait, F.: Forgery detection based on intrinsic document contents. In: Proceedings of the 11th IAPR Workshop on Document Analysis Systems, Tours, France, pp. 252–256. April 2014
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Metadata
Title
Lessons Learned from Automatic Forgery Detection in over 100,000 Invoices
Authors
Joost van Beusekom
Armin Stahl
Faisal Shafait
Copyright Year
2015
Book
Computational Forensics

Print ISBN: 978-3-319-20124-5

Electronic ISBN: 978-3-319-20125-2

Copyright Year: 2015

DOI
https://doi.org/10.1007/978-3-319-20125-2_12

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