Skip to main content

A Head-Mounted Device for Recognizing Text in Natural Scenes

  • Conference paper
Camera-Based Document Analysis and Recognition (CBDAR 2011)

Part of the book series: Lecture Notes in Computer Science ((LNIP,volume 7139))

Abstract

We present a mobile head-mounted device for detecting and tracking text that is encased in an ordinary flat-cap hat. The main parts of the device are an integrated camera and audio webcam together with a simple remote control system, all connected via a USB hub to a laptop. A near to real-time text detection algorithm (around 14 fps for 640×480 images) which uses Maximal Stable Extremal Regions (MSERs) for image segmentation is proposed. Comparative text detection results against the ICDAR 2003 text locating competition database along with performance figures are presented.

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

Access this chapter

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 54.99
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 69.99
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

Institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. Aoki, H., Schiele, B., Pentland, A.: Realtime personal positioning system for wearable computers. In: ISWC 1999, pp. 37–43. IEEE Computer Society, Washington, DC, USA (1999)

    Google Scholar 

  2. Chmiel, J., Stankiewicz, O., Switala, W., Tluczek, M., Jelonek, J.: Read IT project report: A portable text reading system for the blind people (2005)

    Google Scholar 

  3. Donoser, M., Bischof, H.: Efficient maximally stable extremal region (MSER) tracking. In: CVPR 2006, pp. 553–560 (2006)

    Google Scholar 

  4. Donoser, M., Arth, C., Bischof, H.: Detecting, Tracking and Recognizing License Plates. In: Yagi, Y., Kang, S.B., Kweon, I.S., Zha, H. (eds.) ACCV 2007, Part II. LNCS, vol. 4844, pp. 447–456. Springer, Heidelberg (2007)

    Chapter  Google Scholar 

  5. Epshtein, B., Ofek, E., Wexler, Y.: Detecting text in natural scenes with stroke width transform. In: CVPR 2010, pp. 2963–2970 (2010)

    Google Scholar 

  6. Ezaki, N., Kiyota, K., Minh, B., Bulacu, M., Schomaker, L.: Improved text-detection methods for a camera-based text reading system for blind persons. In: ICDAR 2005, pp. 257–261 (2005)

    Google Scholar 

  7. Hedgpeth, T., Black, J.A., Panchanathan, S.: A demonstration of the iCARE portable reader. In: ASSETS 2006, pp. 279–280 (2006)

    Google Scholar 

  8. Kurzweil, R.: The age of spiritual machines: when computers exceed human intelligence. Viking Press (1998)

    Google Scholar 

  9. Liang, J., Doermann, D., Li, H.: Camera-based analysis of text and documents: a survey. IJDAR, 84–104 (2005)

    Google Scholar 

  10. Lucas, S.M., Panaretos, A., Sosa, L., Tang, A., Wong, S., Young, R.: ICDAR 2003 robust reading competitions. In: ICDAR 2003, pp. 682–687 (2003)

    Google Scholar 

  11. Lucas, S.: ICDAR 2005 text locating competition results. In: ICDAR 2005, pp. 80–84 (2005)

    Google Scholar 

  12. Mancas-Thillou, C., Mirmehdi, M.: Super-resolution text using the teager filter. In: CBDAR 2005, pp. 10–16 (2005)

    Google Scholar 

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

    Google Scholar 

  14. Mayol, W.W., Tordoff, B.J., Murray, D.W.: Wearable visual robots. Personal and Ubiquitous Computing 6, 37–48 (2002)

    Article  Google Scholar 

  15. Merino, C., Mirmehdi, M.: A framework towards realtime detection and tracking of text. In: CBDAR 2007, pp. 10–17 (2007)

    Google Scholar 

  16. Myers, G.K., Burns, B.: A robust method for tracking scene text in video imagery. In: CBDAR 2005 (2005)

    Google Scholar 

  17. Neumann, L., Matas, J.: A Method for Text Localization and Recognition in Real-World Images. In: Kimmel, R., Klette, R., Sugimoto, A. (eds.) ACCV 2010, Part III. LNCS, vol. 6494, pp. 770–783. Springer, Heidelberg (2011)

    Chapter  Google Scholar 

  18. Nistér, D., Stewénius, H.: Linear Time Maximally Stable Extremal Regions. In: Forsyth, D., Torr, P., Zisserman, A. (eds.) ECCV 2008, Part II. LNCS, vol. 5303, pp. 183–196. Springer, Heidelberg (2008)

    Chapter  Google Scholar 

  19. Pan, Y.F., Hou, X., Liu, C.L.: Text localization in natural scene images based on conditional random field. In: ICDAR 2009, pp. 6–10 (2009)

    Google Scholar 

  20. Pan, Y.F., Hou, X., Liu, C.L.: A hybrid approach to detect and localize texts in natural scene images. TIP (2011)

    Google Scholar 

  21. Peters, J.P., Thillou, C., Ferreira, S.: Embedded reading device for blind people: a user-centred design. In: AIPR 2004, pp. 217–222 (2004)

    Google Scholar 

  22. Shi, X., Xu, Y.: A wearable translation robot. In: ICRA 2005 (2005)

    Google Scholar 

  23. Targhi, A.T., Hayman, E., Olof Eklundh, J.: Real-time texture detection using the LU-transform. In: CIMCV (2006)

    Google Scholar 

  24. Zhang, J., Kasturi, R.: Extraction of text objects in video documents: Recent progress. In: DAS 2008, pp. 5–17. IEEE Computer Society, Washington, DC, USA (2008)

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2012 Springer-Verlag Berlin Heidelberg

About this paper

Cite this paper

Merino-Gracia, C., Lenc, K., Mirmehdi, M. (2012). A Head-Mounted Device for Recognizing Text in Natural Scenes. In: Iwamura, M., Shafait, F. (eds) Camera-Based Document Analysis and Recognition. CBDAR 2011. Lecture Notes in Computer Science, vol 7139. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-29364-1_3

Download citation

  • DOI: https://doi.org/10.1007/978-3-642-29364-1_3

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-29363-4

  • Online ISBN: 978-3-642-29364-1

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics