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Document inspection using text-line alignment

Published: 09 June 2010 Publication History

Abstract

Passports, ID cards, banknotes, and degrees are considered as valuable documents that need to be secured against forgery. Apart from those, there are many other document types that are valuable, too, but that do not have any security features, as e.g. bills and vouchers. These may be used by fraudulent people to defraud money from e.g. a car insurance company. The wide availability of scanning and printing hardware allows even non-experts to easily forge a document. We therefore present a new aspect in the examination of intrinsic document features for optical document security: the goal is to automatically detect text-lines that have been manipulated or additionally inserted in a document by inspecting their alignment (left, right or center) with respect to the other text-lines in the document. This constitutes an additional feature in the goal of developing a powerful toolbox for automatic document inspection. Using the extracted text-lines, the alignment margins are extracted. Statistics on the distances of the text-lines to the alignment margins are used to identify lines that might have been forged. Such documents can then be presented to a human operator for further inspection. Due to lack of public datasets containing forged documents, a new dataset had to be created. Evaluation showed a classification accuracy of 90.5%.

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Cited By

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  • (2022)Verifying Document IntegrityMultimedia Security 210.1002/9781119987390.ch3(59-89)Online publication date: Jul-2022
  • (2018)Find it! Fraud Detection Contest Report2018 24th International Conference on Pattern Recognition (ICPR)10.1109/ICPR.2018.8545428(13-18)Online publication date: Aug-2018
  • (2017)A dataset for forgery detection and spotting in document images2017 Seventh International Conference on Emerging Security Technologies (EST)10.1109/EST.2017.8090394(26-31)Online publication date: Sep-2017
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    cover image ACM Other conferences
    DAS '10: Proceedings of the 9th IAPR International Workshop on Document Analysis Systems
    June 2010
    490 pages
    ISBN:9781605587738
    DOI:10.1145/1815330
    Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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    Publication History

    Published: 09 June 2010

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    View all
    • (2022)Verifying Document IntegrityMultimedia Security 210.1002/9781119987390.ch3(59-89)Online publication date: Jul-2022
    • (2018)Find it! Fraud Detection Contest Report2018 24th International Conference on Pattern Recognition (ICPR)10.1109/ICPR.2018.8545428(13-18)Online publication date: Aug-2018
    • (2017)A dataset for forgery detection and spotting in document images2017 Seventh International Conference on Emerging Security Technologies (EST)10.1109/EST.2017.8090394(26-31)Online publication date: Sep-2017
    • (2015)Printer and Scanner ForensicsHandbook of Digital Forensics of Multimedia Data and Devices10.1002/9781118705773.ch10(375-410)Online publication date: 18-Dec-2015
    • (2013)A System Based on Intrinsic Features for Fraudulent Document DetectionProceedings of the 2013 12th International Conference on Document Analysis and Recognition10.1109/ICDAR.2013.29(106-110)Online publication date: 25-Aug-2013
    • (2011)Printed text characterization for identifying print technology using expectation maximization algorithmProceedings of the 5th international conference on Multi-Disciplinary Trends in Artificial Intelligence10.1007/978-3-642-25725-4_18(201-212)Online publication date: 7-Dec-2011

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