Skip to main content

Mathematical Morphology and Region Clustering Based Text Information Extraction from Malayalam News Videos

Part of the Advances in Intelligent Systems and Computing book series (AISC,volume 425)

Abstract

Innovations in technologies like improved internet data transfer, advanced digital data compression algorithms, enhancements in web technology, etc. enabled the exponential growth in digital multimedia data. Among the massive multimedia data, news videos are of higher priority due to its rich up-to-date information and historical evidences. This data is rapidly growing in an unpredictable fashion which requires an efficient and powerful method to index and retrieve such massive data. Even though manual indexing is the most effective, it is the slowest and most expensive. Hence automatic video indexing is considered as an important research problem to be addressed uniquely.

In this work, we propose a Mathematical Morphology and Region Clustering based Text Information Extraction (TIE) from Malayalam news videos for Content Based Video Indexing and Retrieval (CBVIR). Morphological gradient acts as an edge detector, by enhancing the intensity variations for detecting the text regions. Further an agglomerative clustering is performed to select the significant text regions. The precision, recall and F1-measure obtained for the proposed approach are 87.45%, 94.85% and 0.91 respectively.

Keywords

  • Mathematical Morphology
  • Text Region
  • Agglomerative Cluster
  • News Video
  • Normalize Cross Correlation

These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

This is a preview of subscription content, access via your institution.

Buying options

Chapter
USD   29.95
Price excludes VAT (USA)
  • DOI: 10.1007/978-3-319-28658-7_37
  • Chapter length: 12 pages
  • Instant PDF download
  • Readable on all devices
  • Own it forever
  • Exclusive offer for individuals only
  • Tax calculation will be finalised during checkout
eBook
USD   269.00
Price excludes VAT (USA)
  • ISBN: 978-3-319-28658-7
  • Instant PDF download
  • Readable on all devices
  • Own it forever
  • Exclusive offer for individuals only
  • Tax calculation will be finalised during checkout
Softcover Book
USD   349.99
Price excludes VAT (USA)

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. Chua, T.-S., Chaisorn, L., Hsu, W., Chang, S.-F., et al.: Story boundary detection in large broadcast news video archives: techniques, experience and trends. In: Proceedings of the 12th Annual ACM International Conference on Multimedia, MULTIMEDIA 2004, pp. 656–659 (2004)

    Google Scholar 

  2. Katayama, N., Satoh, S., Ide, I., Mo, H.: Topic-based inter-video structuring of a large-scale news video corpus. In: International Conference on Multimedia and Expo, vol. 3 (2003)

    Google Scholar 

  3. Lee, C.-H., Chaisorn, L., Chua, T.S.: The segmentation of news video into story units. In: IEEE International Conference on Multimedia and Expo, vol. 1, pp. 73–76 (2002)

    Google Scholar 

  4. Hauptmann, M.J., Witbrock, A.G.: Story segmentation and detection of commercials in broadcast news video. In: IEEE International Forum on, Research and Technology Advances in Digital Libraries, pp. 168–179 (1998)

    Google Scholar 

  5. Ye, J., Hua-yong, L., Jun-qing, Yu., Dong-ru, Z.: Content-based hierarchical analysis of news video using audio and visual information. Wuhan University Journal of Natural Sciences 6(4), 779–783 (2001)

    CrossRef  Google Scholar 

  6. Muller, S., Eickeler, S.: Content-based video indexing of tv broadcast news using hidden markov models. In: IEEE International Conference on Acoustics, Speech, and Signal Processing, vol. 6, pp. 2997–3000 (1999)

    Google Scholar 

  7. Smoliar, S.W., Tan, S.Y., Zhang, H., Gong, Y.: Automatic parsing of news video. In: Proceedings of the International Conference on Multimedia Computing and Systems, pp. 45–54 (1994)

    Google Scholar 

  8. Huang, Q., Liu, Z., Rosenberg, A., Gibbon, D., Shahraray, B.: Automated generation of news content hierarchy by integrating audio, video, and text information. In: IEEE International Conference on Acoustics, Speech, and Signal Processing, vol. 6, pp. 3025–3028, March 1999

    Google Scholar 

  9. Baig, M.N., Asif, M.D.A., Tariq, U.U., Ahmad, W.: A novel hybrid method for text detection and extraction from news videos. Middle-East Journal of Scientific Research (2014). ISSN: 1990-9233, doi:10.5829/idosi.mejsr.2014.19.5.21019

  10. Ariki, Y., Teranishi, T.: Indexing and classification of tv news articles based on telop recognition. Document Analysis and Recognition 1, 422–427 (1997)

    Google Scholar 

  11. Alimi, A.M., Ben Halima, M., Karray, H.: Arabic text recognition in video sequences. In: The International Conference on Informatics, Cybernetics, and Computer Applications, July 2010

    Google Scholar 

  12. Jawahar, C.V., Chennupati, B., Paluri, B., Jammalamadaka, N.: Video retrieval based on textual queries. In: Proceedings of the Thirteenth International Conference on Advanced Computing and Communications, Coimbatore (2005)

    Google Scholar 

  13. Anoop, K., Lajish, V.L.: Morphology based text detection and extraction from Malayalam news videos. In: National Conference on Indian Language Computing. CUSAT (2014)

    Google Scholar 

  14. Pala, P., Bertini, M., Bimbo, A.: Content based indexing and retrieval of tv news. Pattern Recognition Letters, 503–516. Elsevier (2001)

    Google Scholar 

  15. Kelkar, C., Khairnar, N., Gaikwad, H., Hapase, A.: News video segmentation and categorization using text extraction technique. International Journal of Engineering Research and Technology 2(3), March 2013. ISSN: 2278–0181

    Google Scholar 

  16. Hughes, E.K., Smith, M.A., Sato, T., Kanade, T.: Video OCR for digital news archives. In: IEEE Workshop on Content-Based Access of Image and Video Database, Bombay, India, January 1998

    Google Scholar 

  17. Hughes, E.K., Smith, M.A., Satoh, S., Sato, T., Kanade, T.: Video OCR: Indexing digital news libraries by recognition of superimposed captions. Multimedia Systems. Springer (1999)

    Google Scholar 

  18. Liou, S.-P., Zhu, W., Toklu, C.: Automatic news video segmentation and categorization based on closed-captioned text. In: IEEE International Conference on Multimedia and Expo, pp. 829–832, August 2001

    Google Scholar 

  19. Akamatsu, S., Ohya, J., Shio, A.: Recognizing characters in scene images. IEEE Transactions on Pattern Analysis and Machine Intelligence 16(2), 214–220 (1994)

    CrossRef  Google Scholar 

  20. Kankanhalli, A., Lee, C.M.: Automatic extraction of characters in complex images. Int. J. Pattern Recognition Artif. Intell. 9(1), 67–82 (1995)

    CrossRef  Google Scholar 

  21. Kia, O., Li, H., Doerman, D.: Automatic text detection and tracking in digital video. IEEE Trans. Image Process. 9(1), 147–156 (2000)

    CrossRef  Google Scholar 

  22. Jain, A.K., Zhong, Y., Zhang, H.: Automatic caption localization in compressed video. IEEE Trans. Pattern Anal. Mach. Intell. 22(4), 385–392 (2000)

    CrossRef  Google Scholar 

  23. Riseman, E.M., Wu, V., Manmatha, R.: Extfinder: an automatic system to detect and recognize text in images. IEEE Trans. Pattern Anal. Mach. Intell. 21(11), 1224–1229 (1999)

    CrossRef  Google Scholar 

  24. Karam, L.J., Hasan, Y.M.Y.: Morphological text extraction from images. IEEE Transactions on Image Processing 9(11), 1978–1983 (2000)

    CrossRef  Google Scholar 

  25. Ren, T.I., Cavalcanti, G.D.C., dos Santos, R.P., Clemente, G.S.: Text line segmentation based on morphology and histogram projection. In: Proceedings of the 2009 10th International Conference on Document Analysis and Recognition, pp. 651–655

    Google Scholar 

  26. Chandrasekaran, R.M., Chandrasekaran, R.: Morphology based text extraction in images. IJCST 2(4) (2011). ISSN: 0976–8491

    Google Scholar 

  27. Raja Rajeswari, S., Pratheeba, T., Kavith, V.: Morphology based text detection and extraction from complex video scene. International Journal of Engineering and Technology 2(3) (2010).Trans. Pattern Anal. Mach. Intell. 16(2), 214–224 (1994)

    Google Scholar 

  28. Kanade, T., Smith, M.A.: Video skimming for quick browsing based on audio and image characterization, Technical Report CMU-CS-95-186, Carnegie Mellon University, July 1995

    Google Scholar 

  29. Kim, C., Kim, W.: A new approach for overlay text detection and extraction from complex video scene. IEEE Transactions On Image Processing 18(2), February 2009

    Google Scholar 

  30. Lyu, M.R., Song, J., Cai, M.: A comprehensive method for multilingual video text detection, localization, and extraction. IEEE Transactions on Circuits and Systems for Video Technology 15(2), 243–255 (2005)

    CrossRef  Google Scholar 

  31. Hao, X., Ye, J., Huang, L.-L.: Neural network based text detection in videos using local binary patterns. In: Chinese Conference on Pattern Recognition, pp. 1–5 (2009)

    Google Scholar 

  32. Kim, H.-K.: Efficient automatic text location method and content-based indexing and structuring of video database. Journal of Visual Communication and Image Representation. Elsevier. doi:10.1006/jvci.1996.0029

    Google Scholar 

  33. Yu, B., Jain, A.K.: Automatic text location in images and video frames. In: Proceedings. Fourteenth International Conference on Pattern Recognition, vol. 2 (1998)

    Google Scholar 

  34. Nirmala, S., Nagabhushan, P.: Text extraction in complex color document images for enhanced readability. Intelligent Information Management 2, 120–133 (2010)

    CrossRef  Google Scholar 

  35. Jain, A.K., Zhong, Y., Karu, K.: Locating text in complex color images. In: Proceedings of the Third International Conference on Document Analysis and Recognition, vol. 1, pp. 146–149, August 1995

    Google Scholar 

  36. Tremeau, A., Karaoglu, S., Fernando, B.: A novel algorithm for text detection and localization in natural scene images. In: International Conference on Digital Image Computing: Techniques and Applications (2010)

    Google Scholar 

  37. Govardhan, A., Swamy Das, M., Hima Bindhu, B.: Evaluation of text detection and localization methods in natural images. International Journal of Emerging Technology and Advanced Engineering 2(6), June 2012. ISSN 2250–2459

    Google Scholar 

  38. Canedo-Rodriguez, A., Kim, J.H., Kelly, J., Hee Kim, J., Kim, S.H., Blanco-Fernandez, Y., Veeranmachaneni, S.K.: An efficient and accurate text localization algorithm in compressed mobile phone image domain. In: Int. Conf. on Image Processing, Computer Vision, and Pattern Recognition, July 2010

    Google Scholar 

  39. Smoliar, S.W., Tan, S.Y., Zhang, H., Gong, Y.: Automatic parsing of news video, multimedia computing and systems. In: Proceedings of the International Conference, pp. 45–54 (1994)

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to V. L. Lajish .

Editor information

Editors and Affiliations

Rights and permissions

Reprints and Permissions

Copyright information

© 2016 Springer International Publishing Switzerland

About this paper

Cite this paper

Anoop, K., Gangan, M.P., Lajish, V.L. (2016). Mathematical Morphology and Region Clustering Based Text Information Extraction from Malayalam News Videos. In: Thampi, S., Bandyopadhyay, S., Krishnan, S., Li, KC., Mosin, S., Ma, M. (eds) Advances in Signal Processing and Intelligent Recognition Systems. Advances in Intelligent Systems and Computing, vol 425. Springer, Cham. https://doi.org/10.1007/978-3-319-28658-7_37

Download citation

  • DOI: https://doi.org/10.1007/978-3-319-28658-7_37

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-28656-3

  • Online ISBN: 978-3-319-28658-7

  • eBook Packages: EngineeringEngineering (R0)