Skip to main content
SpringerLink
Log in

Word Level Script Identification of Text in Low Resolution Images of Display Boards Using Wavelet Features

  • Conference paper
Proceedings of International Conference on Advances in Computing

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 174))

Abstract

Automated systems for understanding low resolution images of display boards are facilitating several new applications such as blind assistants, tour guide systems, location aware systems and many more. Script identification at character/word level is one of the very important pre-processing steps for development of such systems prior to further image analysis. In this paper, a new approach for word level script identification of text in low resolution images of display boards is presented. The proposed methodology uses horizontal run statistics and wavelet features for distinguishing 5 Indian scripts namely; Hindi, Kannada, English, Malyalam and Tamil. The method works in two phases; In the first phase, the wavelet transform based texture features such as zone wise wavelet energy features, vertical run statistical features of wavelet coefficients and wavelet log mean deviation features of decomposed energy bands at 2 levels are obtained from training word images and knowledge bases are constructed, one for each script/language under study. The second phase is testing, in which test word image is processed to obtain horizontal run statistics to determine whether it belongs to Hindi script. Otherwise, a newly defined descriminant function that measures the city block distance between test sample and pre-constructed knowledge base of every script is used to identify the script of the test sample. The proposed method is robust and insensitive to the variations in size and style of font, number of characters, thickness and spacing between characters, noise, and other degradations. The proposed method achieves an overall identification accuracy of 89.7% and individual identification accuracy of 92% for Kannada Script, 97.67% for English, 82.5% for Malyalam and 87% for Tamil Script.

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

Access this chapter

Log in via an institution
Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 259.00
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 329.99
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. Abowd, D.G., Atkeson, C.G., Hong, J., Long, S., Kooper, R., Pinkerton, M.: CyberGuide: A mobile context-aware tour guide. Wireless Networks 3(5), 421–433 (1997)

    Article  Google Scholar 

  2. Marmasse, N., Schamandt, C.: Location aware information delivery with comMotion. In: Proceedings of Conference on Human Factors in Computing Systems, pp. 157–171 (2000)

    Google Scholar 

  3. Tollmar, K., Yeh, T., Darrell, T.: IDeixis - Image-Based Deixis for Finding Location-Based Information. In: Proceedings of Conference on Human Factors in Computing Systems (CHI 2004), pp. 781–782 (2004)

    Google Scholar 

  4. Leetch, G., Mangina, E.: A Multi-Agent System to Stream Multimedia to Handheld Devices. In: Proceedings of the Sixth International Conference on Computational Intelligence and Multimedia Applications, ICCIMA 2005 (2005)

    Google Scholar 

  5. Premchaiswadi, W.: A mobile Image search for Tourist Information System. In: Proceedings of 9th International Conference on Signal Processing, Computational Geometry and Artificial Vision, pp. 62–67 (2009)

    Google Scholar 

  6. Ma, C.-J., Fang, J.-Y.: Location Based Mobile Tour Guide Services Towards Digital Dunhaung. In: International Archives of Phtotgrammtery, Remote Sensing and Spatial Information Sciences, Beijing, vol. XXXVII, Part B4 (2008)

    Google Scholar 

  7. Wu, S.-H., Li, M.-X., Yanga, P.-C., Kub, T.: Ubiquitous Wikipedia on Handheld Device for Mobile Learning. In: 6th IEEE International Conference on Wireless, Mobile and Ubiquitous Technologies in Education, pp. 228–230 (2010)

    Google Scholar 

  8. Yeh, T., Grauman, K., Tollmar, K.: A picture is worth a thousand keywords: image-based object search on a mobile platform. In: Proceedings of Conference on Human Factors in Computing Systems, pp. 2025–2028 (2005)

    Google Scholar 

  9. Fan, X., Xie, X., Li, Z., Li, M., Ma: Photo-to-search: using multimodal queries to search web from mobile phones. In: Proceedings of 7th ACM SIGMM International Workshop on Multimedia Information Retrieval (2005)

    Google Scholar 

  10. Hwee, L.J., Chevallet, J.P., Merah, S.N.: SnapToTell: Ubiquitous information access from camera. In: Mobile Human Computer Interaction with Mobile Devices and Services, Glasgow, Scotland (2005)

    Google Scholar 

  11. Spitz, A.L.: Determination of Script and Language Content of Document Images. IEEE Trans. Pattern Analysis and Machine Intelligence 19(3), 235–245 (1997)

    Article  Google Scholar 

  12. Pal, U., Chaudhury, B.B.: Identification of Different Script Lines from Multi-Script Documents. Image and Vision Computing 20(13-14), 945–954 (2002)

    Article  Google Scholar 

  13. Shijian, L., Tan, C.L.: Script and Language Identification in Noisy and Degraded Document Images. IEEE Transactions on Pattern Analysis and Machine Intelligence 30(1) (January 2008)

    Google Scholar 

  14. Tan, T.N.: Rotation Invariant Texture Features and Their Use in Automatic Script Identification. IEEE Trans. Pattern Analysis and Machine Intelligence 20(7), 751–756 (1998)

    Article  Google Scholar 

  15. Peake, G.S., Tan, T.N.: Script and Language Identification from Document Images. In: Proc. Eight British Mach. Vision Conf., vol. 2, pp. 230–233 (September 1997)

    Google Scholar 

  16. Busch, A., Boles, W.W., Sridharan, S.: Texture for Script Identification. IEEE Trans. Pattern Analysis and Machine Intelligence 27(11), 1720–1732 (2005)

    Article  Google Scholar 

  17. Hiremath, P.S., et al.: Script identification in a handwritten document image using texture features. In: IEEE 2nd International Advance Computing Conference, pp. 110–114 (2010)

    Google Scholar 

  18. Hochberg, J., Kerns, L., Kelly, P., Thomas, T.: Automatic Script Identification from Images Using Cluster-Based Templates. IEEE Trans. Pattern Analysis and Machine Intelligence 19(2), 176–181 (1997)

    Article  Google Scholar 

  19. Vikram, T.N., Chidananada Gowda, K., Shalini, R.: “Symbolic representation of Kannada characters for recognition. In: IEEE Conference on.., pp. 823–826

    Google Scholar 

  20. Angadi, S.A.: Intelligent Integrated Automation System for Efficient processing of Postal Mail, PhD thesis submitted to Department of Studies in Computer Science. University of Mysore (2007)

    Google Scholar 

  21. Li, L., Tan, C.L.: Script identification of camera-based images. In: 19th International Conference on Pattern Recognition, ICPR 2008, December 8-11, pp. 1–4 (2008), doi:10.1109/ICPR.2008.4760965

    Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Department of Computer Science and Engineering, Basaveshwar Engineering College, Bagalkot, 587102, Karnataka, India

    S. A. Angadi & M. M. Kodabagi

Authors
  1. S. A. Angadi
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. M. M. Kodabagi
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to S. A. Angadi .

Editor information

Editors and Affiliations

  1. M. S. Ramaiah Institute of Technology, Bengaluru, India

    Aswatha Kumar M.

  2. M. S. Ramaiah Institute of Technology, Bengaluru, India

    Selvarani R.

  3. M. S. Ramaiah Institute of Technology, Bengaluru, India

    T V Suresh Kumar

Rights and permissions

Reprints and permissions

Copyright information

© 2013 Springer India

About this paper

Cite this paper

Angadi, S.A., Kodabagi, M.M. (2013). Word Level Script Identification of Text in Low Resolution Images of Display Boards Using Wavelet Features. In: Kumar M., A., R., S., Kumar, T. (eds) Proceedings of International Conference on Advances in Computing. Advances in Intelligent Systems and Computing, vol 174. Springer, New Delhi. https://doi.org/10.1007/978-81-322-0740-5_26

Download citation

  • DOI: https://doi.org/10.1007/978-81-322-0740-5_26

  • Publisher Name: Springer, New Delhi

  • Print ISBN: 978-81-322-0739-9

  • Online ISBN: 978-81-322-0740-5

  • eBook Packages: EngineeringEngineering (R0)

Publish with us

Policies and ethics

Search

Navigation