Skip to main content

Advertisement

Springer Nature Link
Log in

Text-line examination for document forgery detection

  • Original Paper
  • Published:
International Journal on Document Analysis and Recognition (IJDAR) Aims and scope Submit manuscript

Abstract

In this paper, an approach for forgery detection using text-line information is presented. In questioned document examination, text-line rotation and alignment can be important clues for detecting tampered documents. Measuring and detecting such mis-rotations and mis-alignments are a cumbersome task. Therefore, an automated approach for verification of documents based on these two text-line features is proposed in this paper. An in-depth evaluation of the proposed methods shows its usefulness in the context of document security with an area under the ROC curve (AUC) score of AUC=0.89. The automatic nature of the approach allows the presented methods to be used in high-volume environments.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Subscribe and save

Springer+ Basic
$34.99 /Month
  • Get 10 units per month
  • Download Article/Chapter or eBook
  • 1 Unit = 1 Article or 1 Chapter
  • Cancel anytime
Subscribe now

Buy Now

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Similar content being viewed by others

References

  1. Lindblom B.S., Gervais R.: Scientific Examination of Ques- tioned Documents, pp. 238–241. Taylor and Francis, Boca Raton, FL (2006)

    Google Scholar 

  2. Smith, P.J., O’Doherty, P., Luna, C., McCarthy, S.: Commercial anticounterfeit products using machine vision. In: Proceedings of SPIE Optical Security and Counterfeit Deterrence Techniques V, vol. 5310, pp. 237–243. San Jose, CA, USA (2004)

  3. Amidror, I.: A new print-based security strategy for the protection of valuable documents and products using moire intensity profiles. In: Proceedings of SPIE Optical Security and Counterfeit Deterrence Techniques IV, vol. 4677, pp. 89–100. San Jose, CA, USA (2002)

  4. Hampp, N.A., Neebe, M., Juchem T., Wolperdinger M., Geiger M., Schmuck A.: Multifunctional optical security features based on bacteriorhodopsin. In: Proceedings of SPIE Optical Security and Counterfeit Deterrence Techniques V, vol. 5310, pp. 117–124. San Jose, CA, USA (2004)

  5. van Renesse, R.: Ordering the order, a survey of optical document security features. In: Proceedings of SPIE Conference on Practical Holography IX, pp. 268–275. San Jose, CA, USA (1995)

  6. van Renesse, R.: Protection of high security documents—developments in holography to secure the future market and serve the public. In: Proceedings of Holo-Pack, Holo-Print, Vienna, Austria (2006)

  7. van Renesse, R.: Hidden and scambled images—a review. In: Proceedings of SPIE Optical Security and Counterfeit Deterrence Techniques IV, vol. 4677, pp. 333–348. San Jose, CA, USA (2002)

  8. Ali, G.N., Chiang, P.-J., Mikkilineni, A.K., Allebach, J.P., Chiu, G.T.C., Delp, E.J.: Intrinsic and extrinsic signatures for information hiding and secure printing with electrophotographic devices. In: Proceedings of the International Conference on Digital Printing Technologies, pp. 511–515. New Orleans, LA, USA (2003)

  9. Mikkilineni, A.K., Chiang, P.-J., Ali, G.N., Chiu, G.T.C., Allebach, J.P., Delp, E.J.: Printer identification based on graylevel co-occurrence features for security and forensic applications. In: Proceedings of SPIE Security, Steganography, and Watermarking of Multimedia Contents VII, vol. 5681, pp. 430–440. San Jose, CA, USA (2005)

  10. Khanna, N., Mikkilineni, A.K., Chiu, G.T.C., Allebach, J.P., Delp, E.J.: Survey of scanner and printer forensics at purdue university. In: Proceedings of the 2nd International Workshop on Computational Forensics. Lecture Notes in Computer Science, vol. 5158, pp. 22–34. Washington, DC, USA (2008)

  11. Schulze, C., Schreyer, M., Stahl, A., Breuel, T.M.: Evaluation of graylevel-features for printing technique classification in high-throughput document management systems. In: Proceedings of the 2nd International Workshop on Computational Forensics. Lecture Notes in Computer Science, vol. 5158, pp. 35–46. Washington, DC, USA (2008)

  12. Schreyer, M.: Intelligent printing technique recognition and photocopy detection for forensic document examination. In: Proceedings of Informatiktage 2009, vol. S-8, pp. 39–42. Bonn, Germany (2009)

  13. Schulze, C., Schreyer, M., Stahl, A., Breuel, T.M.: Using DCT features for printing technique and copy detection. In: Proceedings of the 5th International Conference on Digital Forensics, pp. 95–106. Orlando, FL, USA (2009)

  14. Breuel, T.M.: Robust least square baseline finding using a branch and bound algorithm. In: Proceedings of SPIE Document Recognition and Retrieval IX, pp. 20–27. San Jose, CA, USA (2002)

  15. Shafait F., Keysers D., Breuel T.M.: Performance evaluation and benchmarking of six page segmentation algorithms. IEEE Trans. Pattern Anal. Mach. Intell. 30(6), 941–954 (2008)

    Article  Google Scholar 

  16. van Beusekom J., Shafait F., Breuel T.M.: Combined orientation and skew detection using geometric text-line modeling. Int. J. Doc. Anal. Recognit. 13(2), 79–92 (2010)

    Article  Google Scholar 

  17. Kanungo T., Haralick R.M.: An automatic closed-loop methodology for generating character groundtruth for scanned documents. IEEE Trans. Pattern Anal. Mach. Intell. 21(2), 179–183 (1999)

    Article  Google Scholar 

  18. Breuel T.M.: On the use of interval arithmetic in geometric branch-and-bound algorithms. Pattern Recognit. Lett. 24(9–10), 1375–1384 (2003)

    Article  MATH  Google Scholar 

  19. Duda, R.O., Hart, P. E., Stork, D. G.: Pattern Classification, p. 49. Wiley, New York (2001)

  20. van Beusekom, J., Shafait, F., Breuel, T.M.: Document signature using intrinsic features for counterfeit detection. In: Proceedings of the 2nd International Workshop on Computational Forensics. Lecture Notes in Computer Science, vol. 5158, pp. 47–57. Washing-ton, DC, USA (2008)

Download references

Author information

Authors and Affiliations

  1. Department of Computer Science, University of Kaiserslautern, Image Understanding and Pattern Recognition Group, 67663, Kaiserslautern, Germany

    Joost van Beusekom & Thomas M. Breuel

  2. German Research Center for Artificial Intelligence (DFKI), 67663, Kaiserslautern, Germany

    Joost van Beusekom & Faisal Shafait

Authors
  1. Joost van Beusekom
    View author publications

    You can also search for this author inPubMed Google Scholar

  2. Faisal Shafait
    View author publications

    You can also search for this author inPubMed Google Scholar

  3. Thomas M. Breuel
    View author publications

    You can also search for this author inPubMed Google Scholar

Corresponding author

Correspondence to Joost van Beusekom.

Rights and permissions

Reprints and permissions

About this article

Cite this article

van Beusekom, J., Shafait, F. & Breuel, T.M. Text-line examination for document forgery detection. IJDAR 16, 189–207 (2013). https://doi.org/10.1007/s10032-011-0181-5

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s10032-011-0181-5

Keywords