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Industrial Conference on Data Mining

ICDM 2006: Advances in Data Mining. Applications in Medicine, Web Mining, Marketing, Image and Signal Mining pp 431–443Cite as

Mining Dichromatic Colours from Video

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Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 4065))

Abstract

It is commonly accepted that the most powerful approaches for increasing the efficiency of visual content delivery are personalisation and adaptation of visual content according to user’s preferences and his/her individual characteristics. In this work, we present results of a comparative study of colour contrast and characteristics of colour change between successive video frames for normal vision and two most common types of colour blindness: the protanopia and deuteranopia. The results were obtained by colour mining from three videos of different kind including their original and simulated colour blind versions. Detailed data regarding the reduction of colour contrast, decreasing of the number of distinguishable colours, and reduction of inter-frame colour change rate in dichromats are provided.

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References

  1. Hanjalić, A.: Content-based analysis of digital video, 194 p. Kluwer Academic Publisher, Boston (2004)

    MATH  Google Scholar 

  2. Tseng, B.L., Lin, C.-Y., Smith, J.R.: Using MPEG-7 and MPEG-21 for personalizing video. IEEE Trans. Multimedia 11, 42–52 (2004)

    Article  Google Scholar 

  3. Wu, M.Y., Ma, S., Shu, W.: Scheduled video delivery — a scalable on-demand video delivery scheme. IEEE Trans. Multimedia 8, 179–187 (2006)

    Article  Google Scholar 

  4. Feiten, B., Wolf, I., Oh, E., Seo, J., Kim, H.K.: Audio adaptation according to usage environment and perceptual quality metrics. IEEE Trans. Multimedia 7, 446–453 (2005)

    Article  Google Scholar 

  5. Smeulders, A.W.M., Worring, M., Santini, S., Gupta, A., Jain, R.: Content-based image retrieval at the end of the early years. IEEE Trans. Pattern Analysis Mach. Intel. 22, 1349–1380 (2000)

    Article  Google Scholar 

  6. Vetro, A., Timmerer, C.: Digital item adaptation: overview of standardization and research activities. IEEE Trans. Multimedia 7, 418–426 (2005)

    Article  Google Scholar 

  7. Nam, J., Ro, Y.M., Huh, Y., Kim, M.: Visual content adaptation according to user perception characteristics. IEEE Trans. Multimedia 7, 435–445 (2005)

    Article  Google Scholar 

  8. Ghinea, G., Thomas, J.P.: Quality of perception: user quality of service in multimedia presentations. IEEE Trans. Multimedia 7, 786–789 (2005)

    Article  Google Scholar 

  9. ISO: Information Technology. Multimedia Framework. Part 7: Digital item adaptation. ISO/IEC 21000–7 (2004)

    Google Scholar 

  10. Bozdogan, H. (ed.): Statistical Data Mining and Knowledge Discovery, 624 p. Chapman & Hall/CRC Press, Boca Raton (2004)

    MATH  Google Scholar 

  11. Abbass, H.A., Sarker, R.A., Newton, C.S. (eds.): Data Mining: A Heuristic Approach, 310 p. Idea Group Publishing, Hershey (2002)

    Google Scholar 

  12. Zhu, X., Wu, X., Elmagarmid, A.K., Feng, Z., Wu, L.: Video data mining: Semantic indexing and event detection from the association perspective. IEEE Trans. Knowl. Data Eng. 17, 665–677 (2005)

    Article  Google Scholar 

  13. Joyce, R.A., Liu, B.: Temporal segmentation of video using frame and histogram space. IEEE Trans. Multimedia 8, 130–140 (2006)

    Article  Google Scholar 

  14. Manjunath, B.S., Ohm, J.R., Vasudevan, V.V., Yamada, A.: Color and texture descriptors. IEEE Trans. Circ. Syst. Video Technol. 11, 703–715 (2001)

    Article  Google Scholar 

  15. Ferman, A.M., Tekalp, A.M., Mehrotra, R.: Robust color histogram descriptors for video segment retrieval and identification. IEEE Trans. Image Proc. 11, 497–508 (2002)

    Article  Google Scholar 

  16. Huang, J., Kumar, S.R., Mitra, M., Zhu, W.J., Zabih, R.: Image indexing using color correlograms. In: 16th IEEE Conf. on Computer Vision and Pattern Recognition, San Juan, Puerto Rico, pp. 762–768 (1997)

    Google Scholar 

  17. Kovalev, V., Volmer, S.: Color co-occurrence descriptors for querying-by-example. In: Int. Conf. on Multimedia Modelling, Lausanne, Switzerland, pp. 32–38. IEEE Computer Society Press, Los Alamitos (1998)

    Google Scholar 

  18. Lee, H.Y., Lee, H.K., Ha, Y.H.: Spatial color descriptor for image retrieval and video segmentation. IEEE Trans. Multimedia 5, 358–367 (2003)

    Article  Google Scholar 

  19. Viénot, F., Brettel, H., Ott, L., M’Barek, A.B., Mollon, J.: What do color-blind people see? Nature 376, 127–128 (1995)

    Article  Google Scholar 

  20. Rigden, C.: The eye of the beholder - designing for colour-blind users. British Telecom Engineering 17, 2–6 (1999)

    Google Scholar 

  21. Brettel, H., Viénot, F., Mollon, J.: Computerized simulation of color appearance for dichromats. Journal Optical Society of America 14, 2647–2655 (1997)

    Article  Google Scholar 

  22. Viénot, F., Brettel, H., Mollon, J.: Digital video colourmaps for checking the legibility of displays by dichromats. Color Research Appl. 24, 243–252 (1999)

    Article  Google Scholar 

  23. Meyer, G.W., Greenberg, D.P.: Color-defective vision and computer graphics displays. IEEE Computer Graphics and Applications 8, 28–40 (1988)

    Article  Google Scholar 

  24. Kovalev, V.A.: Towards image retrieval for eight percent of color-blind men. In: 17th Int. Conf. On Pattern Recognition (ICPR 2004), Cambridge, UK, vol. 2, pp. 943–946. IEEE Computer Society Press, Los Alamitos (2004)

    Chapter  Google Scholar 

  25. Kovalev, V.A., Petrou, M.: Optimising the choice of colours of an image database for dichromats. In: Perner, P., Imiya, A. (eds.) MLDM 2005. LNCS, vol. 3587, pp. 456–465. Springer, Heidelberg (2005)

    Chapter  Google Scholar 

  26. Walraven, J., Alferdinck, J.W.: Color displays for the color blind. In: ISandT/SID Fifth Color Imaging Conference: Color Science, Systems and Appl., Scottsdale, Arizona, pp. 17–22 (1997)

    Google Scholar 

  27. Becker, R.A., Chambers, J.M., Wilks, A.R.: The New S Language. Chapman and Hall, New York (1988)

    MATH  Google Scholar 

  28. Everitt, B.: A Handbook of Statistical Analyses Using S-Plus, 2nd edn., 256 p. Chapman & Hall/CRC Press, Boca Raton (2002)

    MATH  Google Scholar 

  29. Hunt, R.W.G.: Measuring Color, 2nd edn. Science and Industrial Technology. Ellis Horwood, New York (1991)

    Google Scholar 

  30. Sharma, G.: Digital Color Imaging Handbook. Electrical Engineering & Applied Signal Processing, vol. 11, 800 p. CRC Press LLC, New York (2003)

    Google Scholar 

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Author information

Authors and Affiliations

  1. Centre for Vision, Speech and Signal Processing, School of Electronics and Physical Sciences, University of Surrey, Guildford, Surrey, GU2 7XH, United Kingdom

    Vassili A. Kovalev

Authors
  1. Vassili A. Kovalev
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Editor information

Editors and Affiliations

  1. Institute of Computer Vision and applied Computer Sciences, IBaI, Germany

    Petra Perner

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© 2006 Springer-Verlag Berlin Heidelberg

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Kovalev, V.A. (2006). Mining Dichromatic Colours from Video. In: Perner, P. (eds) Advances in Data Mining. Applications in Medicine, Web Mining, Marketing, Image and Signal Mining. ICDM 2006. Lecture Notes in Computer Science(), vol 4065. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11790853_34

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  • DOI: https://doi.org/10.1007/11790853_34

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-36036-0

  • Online ISBN: 978-3-540-36037-7

  • eBook Packages: Computer ScienceComputer Science (R0)

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