Skip to main content

AR-Based Hologram Detection on Security Documents Using a Mobile Phone

  • Conference paper

Part of the book series: Lecture Notes in Computer Science ((LNIP,volume 8888))

Abstract

Holograms are used frequently in creating fraud resistant security documents, such as passports, ID cards or banknotes. The key contribution of this paper is a real time method to automatically detect holograms in images acquired with a standard smartphone. Following a robust algorithm for creating a tracking target, our approach evaluates an evolving stack of observations of the document to automatically determine the location and size of holograms. We demonstrate the plausibility of our method using a variety of security documents, which are common in everyday use. Finally, we show how suitable data can be captured in a novel mobile gaming experience and draw the link between serious applications and entertainment.

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

Buying options

Chapter
USD   29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD   84.99
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD   109.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Learn about institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. Van Renesse, R.: Optical document security. Optoelectronics Library. Artech House (2005)

    Google Scholar 

  2. Buraga-Lefebvre, C., Coëtmellec, S., Lebrun, D., Özkul, C.: Application of wavelet transform to hologram analysis: three-dimensional location of particles. Optics and Lasers in Engineering 33, 409–421 (2000)

    Article  Google Scholar 

  3. Janucki, J., Owsik, J.: A Wiener filter based correlation method intended to evaluate effectiveness of holographic security devices. Optics Communications 218, 221–228 (2003)

    Article  Google Scholar 

  4. Kwon, H.J., Park, T.H.: An automatic inspection system for hologram with multiple patterns. In: SICE, Annual Conference, pp. 2663–2666 (2007)

    Google Scholar 

  5. Park, T.H., Kwon, H.-J.: Vision inspection system for holograms with mixed patterns. In: IEEE Conference on Automation Science and Engineering (CASE), pp. 563–567 (2010)

    Google Scholar 

  6. Pramila, A., Keskinarkaus, A., Rahtu, E., Seppänen, T.: Watermark recovery from a dual layer hologram with a digital camera. In: Heyden, A., Kahl, F. (eds.) SCIA 2011. LNCS, vol. 6688, pp. 146–155. Springer, Heidelberg (2011)

    Chapter  Google Scholar 

  7. Ren, P., Wang, J., Snyder, J., Tong, X., Guo, B.: Pocket reflectometry. ACM Trans. Graph. 30, 45:1–45:10 (2011)

    Google Scholar 

  8. Dong, Y., Wang, J., Tong, X., Snyder, J., Lan, Y., Ben-Ezra, M., Guo, B.: Manifold bootstrapping for svbrdf capture. In: ACM SIGGRAPH, 98:1–98:10 (2010)

    Google Scholar 

  9. Jachnik, J., Newcombe, R.A., Davison, A.J.: Real-time surface light-field capture for augmentation of planar specular surfaces. In: ISMAR, pp. 91–97 (2012)

    Google Scholar 

  10. Hartl, A., Grubert, J., Schmalstieg, D., Reitmayr, G.: Mobile interactive hologram verification. In: ISMAR, pp. 75–82 (2013)

    Google Scholar 

  11. Hartl, A., Reitmayr, G.: Rectangular target extraction for mobile augmented reality applications. In: Proceedings of the International Conference on Pattern Recognition, pp. 81–84 (2012)

    Google Scholar 

  12. Wagner, D., Reitmayr, G., Mulloni, A., Drummond, T., Schmalstieg, D.: Real-time detection and tracking for augmented reality on mobile phones. TVCG 16, 355–368 (2010)

    Google Scholar 

  13. Shafait, F., Keysers, D., Breuel, T.: Efficient implementation of local adaptive thresholding techniques using integral images. In: DRR, SPIE (2008)

    Google Scholar 

  14. Bataineh, B., Abdullah, S.N.H.S., Omar, K.: An adaptive local binarization method for document images based on a novel thresholding method and dynamic windows. Pattern Recogn. Lett. 32, 1805–1813 (2011)

    Article  Google Scholar 

  15. van Beusekom, J., Keysers, D., Shafait, F., Breuel, T.: Distance measures for layout-based document image retrieval. In: Int. Conference on Document Image Analysis for Libraries (DIAL), vol. 11, p. 242 (2006)

    Google Scholar 

  16. Matas, J., Chum, O., Urban, M., Pajdla, T.: Robust wide baseline stereo from maximally stable extremal regions. In: BMVC, 36.1–36.10 (2002)

    Google Scholar 

  17. Comaniciu, D., Meer, P.: Mean shift: a robust approach toward feature space analysis. PAMI 24, 603–619 (2002)

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2014 Springer International Publishing Switzerland

About this paper

Cite this paper

Hartl, A., Arth, C., Schmalstieg, D. (2014). AR-Based Hologram Detection on Security Documents Using a Mobile Phone. In: Bebis, G., et al. Advances in Visual Computing. ISVC 2014. Lecture Notes in Computer Science, vol 8888. Springer, Cham. https://doi.org/10.1007/978-3-319-14364-4_32

Download citation

  • DOI: https://doi.org/10.1007/978-3-319-14364-4_32

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-14363-7

  • Online ISBN: 978-3-319-14364-4

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics