Nothing Special   »   [go: up one dir, main page]

Skip to main content

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 331))

  • 2209 Accesses

Abstract

This paper outlines a simple and practical technique for detecting logos characterizing a broadcast station in TV Programme. Traditional detecting algorithms such as feature extraction and template matching has been applied in many applications. However the limitation of these method cannot recognize the transparent logo effectively. More sophisticated learning-based methods have been address these issues, but they typically involve very high computational complexity. We present an automatic TV logo detection method based statistical property of video sequences. Different other approaches, a transparency factor is introduced firstly in this paper. It is a symbol that responses the level of TV logo transparency and indispensability as a part of the logo information. Combined with the statistical property of video sequences, the logo information can be obtained and detected clearly. Experimental results show that the proposed method not only simple, but gives performs well.

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

Access this chapter

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

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 39.99
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 54.99
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.

Similar content being viewed by others

References

  1. Soysal, M., Ates, T.K., Saracoglu, A., Aydin Alatan, A.: A fast method for animated TV logo detection. In: Content-Based Multimedia Indexing, CBMI 2008, pp. 236–241. IEEE Press, New York (2008)

    Google Scholar 

  2. Zhang, L., Xia, T., Zhang, Y., Li, J.: Hollow TV Logo Detection. In: 2011 18th IEEE International Conference on Image Processing, pp. 3581–3584. IEEE Press, New York (2011)

    Chapter  Google Scholar 

  3. Ozay, N., Sankur, B.: Automatic TV Logo Detection and Classification in Broadcast Videos. In: 17th European Signal Processing Conference (EUSIPCO 2009), Glasgow, Scotland, pp. 839–843 (2009)

    Google Scholar 

  4. Meisinger, K., Troeger, T., Zeller, M., Kaup, A.: Automatic TV Logo Removal Using Statistical Based Logo Detection and Frequency Selective Inpainting. In: Proc. European Signal Processing Conference 2005 (September 2005)

    Google Scholar 

  5. Xiao, G., Dong, Y., Liu, Z., Wang, H.: Supervised TV Logo Detection Based on SVMS. In: Proceedings of IC-NIDC 2010, pp. 174–178. IEEE Press, New York (2010)

    Google Scholar 

  6. Co’zar, J.R., Guil, N., Gonzalez-Linares, J.M., Zapata, E.L.: Video Cataloging Based on Robust Logotype Detection. In: 2006 IEEE International Conference on Image Processing, pp. 3217–3220. IEEE Press, New York (2006)

    Chapter  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

Fan, T., Peng, J., Zhao, H., Wang, G. (2012). An Automatic TV LOGO Detecting Method. In: Zhang, W., Yang, X., Xu, Z., An, P., Liu, Q., Lu, Y. (eds) Advances on Digital Television and Wireless Multimedia Communications. Communications in Computer and Information Science, vol 331. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-34595-1_33

Download citation

  • DOI: https://doi.org/10.1007/978-3-642-34595-1_33

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-34594-4

  • Online ISBN: 978-3-642-34595-1

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics