Real-time Detection and Recognition of Machine-Readable Zones with Mobile Devices

Andreas Hartl, Clemens Arth, Dieter Schmalstieg

Abstract

Many security documents contain machine readable zones (MRZ) for automatic inspection. An MRZ is intended to be read by dedicated machinery, which often requires a stationary setup. Although MRZ information can also be read using camera phones, current solutions require the user to align the document, which is rather tedious. We propose a real-time algorithm for MRZ detection and recognition on off-the-shelf mobile devices. In contrast to state-of-the-art solutions, we do not impose position restrictions on the document. Our system can instantly produce robust reading results from a large range of viewpoints, making it suitable for document verification or classification. We evaluate the proposed algorithm using a large synthetic database on a set of off-the-shelf smartphones. The obtained results prove that our solution is capable of achieving good reading accuracy despite using largely unconstrained viewpoints and mobile devices.

References

  1. Í lvaro Gonzalez, Bergasa, L. M., Torres, J. J. Y., and Bronte, S. (2012). Text location in complex images. In ICPR, pages 617-620.
  2. Bataineh, B., Abdullah, S. N. H. S., and Omar, K. (2011). An adaptive local binarization method for document images based on a novel thresholding method and dynamic windows. Pattern Recogn. Lett., 32(14):1805- 1813.
  3. Donoser, M., Arth, C., and Bischof, H. (2007). Detecting, tracking and recognizing license plates. In ACCV, pages 447-456, Berlin, Heidelberg. Springer-Verlag.
  4. Epshtein, B., Ofek, E., and Wexler, Y. (2010). Detecting text in natural scenes with stroke width transform. In CVPR, pages 2963-2970.
  5. Fabrizio, J., Cord, M., and Marcotegui, B. (2009a). Text extraction from street level images. In CMRT, pages 199-204.
  6. Fabrizio, J., Marcotegui, B., and Cord, M. (2009b). Text segmentation in natural scenes using toggle-mapping. In ICIP, pages 2349-2352.
  7. Hu, J., Kashi, R., and Wilfong, G. (1999). Document classification using layout analysis. In 1999. Proceedings of the International Workshop on Database and Expert Systems Applications, pages 556-560.
  8. ICAO (2008). Machine readable travel documents.
  9. Kasar, T. and Ramakrishnan, A. G. (2012). Multi-script and multi-oriented text localization from scene images. In CBDAR, pages 1-14, Berlin, Heidelberg. SpringerVerlag.
  10. Liu, X., Lu, K., , and Wang, W. (2012). Effectively localize text in natural scene images. In ICPR.
  11. Liu, Z. and Sarkar, S. (2008). Robust outdoor text detection using text intensity and shape features. In ICPR.
  12. Matas, J., Chum, O., Urban, M., and Pajdla, T. (2002). Robust wide baseline stereo from maximally stable extremal regions. In BMVC, pages 36.1-36.10.
  13. Merino-Gracia, C., Lenc, K., and Mirmehdi, M. (2012). A head-mounted device for recognizing text in natural scenes. In CBDAR, pages 29-41, Berlin, Heidelberg. Springer-Verlag.
  14. Minetto, R., Thome, N., Cord, M., Fabrizio, J., and Marcotegui, B. (2010). Snoopertext: A multiresolution system for text detection in complex visual scenes. In ICIP, pages 3861-3864.
  15. Minetto, R., Thome, N., Cord, M., Stolfi, J., Precioso, F., Guyomard, J., and Leite, N. J. (2011). Text detection and recognition in urban scenes. In ICCV Workshops, pages 227-234.
  16. Mishra, A., Alahari, K., and Jawahar, C. V. (2012). Topdown and bottom-up cues for scene text recognition. In CVPR.
  17. Neumann, L. and Matas, J. (2011). Text localization in real-world images using efficiently pruned exhaustive search. In ICDAR, pages 687-691. IEEE.
  18. Neumann, L. and Matas, J. (2012). Real-time scene text localization and recognition. In CVPR, pages 3538- 3545.
  19. Pan, Y.-F., Hou, X., and Liu, C.-L. (2011). A hybrid approach to detect and localize texts in natural scene images. IEEE Transactions on Image Processing, 20(3):800-813.
  20. Saoi, T., Goto, H., and Kobayashi, H. (2005). Text detection in color scene images based on unsupervised clustering of multi-channel wavelet features. In ICDAR, pages 690-694. IEEE Computer Society.
  21. Shafait, F., Keysers, D., and Breuel, T. (2008). Efficient implementation of local adaptive thresholding techniques using integral images. In SPIE DRR. SPIE.
  22. Sun, Q., Lu, Y., and Sun, S. (2010). A visual attention based approach to text extraction. In ICPR, pages 3991- 3995.
  23. Tarjan, R. E. (1972). Depth-first search and linear graph algorithms. SIAM Journal on Computing, 1(2):146- 160.
  24. Wagner, D., Reitmayr, G., Mulloni, A., Drummond, T., and Schmalstieg, D. (2010). Real-time detection and tracking for augmented reality on mobile phones. TVCG, 16(3):355-368.
  25. Yi, C. and Tian, Y. (2011). Text string detection from natural scenes by structure-based partition and grouping. IEEE Transactions on Image Processing, 20(9):2594- 2605.
  26. Zhu, K.-h., Qi, F.-h., Jiang, R.-j., and Xu, L. (2007). Automatic character detection and segmentation in natural scene images. Journal of Zhejiang University SCIENCE A (JZUS), 8(1):63-71.
Download


Paper Citation


in Harvard Style

Hartl A., Arth C. and Schmalstieg D. (2015). Real-time Detection and Recognition of Machine-Readable Zones with Mobile Devices . In Proceedings of the 10th International Conference on Computer Vision Theory and Applications - Volume 3: VISAPP, (VISIGRAPP 2015) ISBN 978-989-758-091-8, pages 79-87. DOI: 10.5220/0005294700790087


in Bibtex Style

@conference{visapp15,
author={Andreas Hartl and Clemens Arth and Dieter Schmalstieg},
title={Real-time Detection and Recognition of Machine-Readable Zones with Mobile Devices},
booktitle={Proceedings of the 10th International Conference on Computer Vision Theory and Applications - Volume 3: VISAPP, (VISIGRAPP 2015)},
year={2015},
pages={79-87},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0005294700790087},
isbn={978-989-758-091-8},
}


in EndNote Style

TY - CONF
JO - Proceedings of the 10th International Conference on Computer Vision Theory and Applications - Volume 3: VISAPP, (VISIGRAPP 2015)
TI - Real-time Detection and Recognition of Machine-Readable Zones with Mobile Devices
SN - 978-989-758-091-8
AU - Hartl A.
AU - Arth C.
AU - Schmalstieg D.
PY - 2015
SP - 79
EP - 87
DO - 10.5220/0005294700790087