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Fuzzy-Based Motion Detection and Its Application to De-Interlacing

  • Dimitri Van De Ville
  • Wilfried Philips
  • Ignace Lemahieu
Part of the Studies in Fuzziness and Soft Computing book series (STUDFUZZ, volume 52)

Summary

This chapter presents a motion detector for interlaced video based on the principles of fuzzy logic control. Interlaced video exhibits several possible artifacts such as line flicker and line crawling. De-interlacing algorithms convert interlaced to progressive scan video formats by interpolating the missing lines. These algorithms can be used to improve picture quality but are also necessary to display interlaced video on progressive output devices. A good de-interlacing technique should adapt to the presence of motion. This chapter presents a motion adaptive de-interlacing technique incorporating a fuzzy motion detector and investigate how the quality of the results depends on the parameters of the technique. We also compare the technique numerically to other de-interlacing methods on several test-sequences.

Keywords

Membership Function Fuzzy Logic Controller Fuzzy Logic Control Fuzzy Rule Base Static Scene 
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.

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References

  1. 1.
    Blume H., Franzen O. and Schmidt M., Optimizing video signal processing algorithms by evolution strategies, Computational Intelligence, No. 1226, pp. 547–548, 1997Google Scholar
  2. 2.
    Booth S., Digital TV in the US, IEEE Spectrum 36, No. 3, pp. 39–46, 1999CrossRefGoogle Scholar
  3. 3.
    Clarke C., Future television systems: Comparison of sequential and interlaced scanning, BBC Research and Development Report, No. 1987/18, 1987Google Scholar
  4. 4.
    Connor D.J., Haskell B.G. and Mounts F.W., A Frame-to-Frame Picturephone Coder for Signals Containing Differential Quantizing Noise, The Bell System Technical Journal, Vol. 52, No. 1, pp. 35–51, 1973Google Scholar
  5. 5.
    Cox E., Fuzzy Fundamentals, IEEE Spectrum, Vol. 29, No. 10, pp. 58–61, 1992CrossRefGoogle Scholar
  6. 6.
    De Haan G. and Bellers E., De-interlacing - An Overview, Proceedings of the IEEE, Vol. 86, No. 9, pp. 1839–1857, 1998CrossRefGoogle Scholar
  7. 7.
    Haavisto P., Juhola J. and Neuvo Y., Fractional frame rate up-conversion using weighted median filters, IEEE Transactions on Consumer Electronics, Vol. 35, No. 3, pp. 272–278, 1989CrossRefGoogle Scholar
  8. 8.
    Haavisto P. and Neuvo Y., Motion Adaptive Scan Rate Up-conversion, Multidimensional Systems Signal Processing, No. 3, pp. 113–130, 1992CrossRefGoogle Scholar
  9. 9.
    Huang T. S., “Image Sequence Analysis”, Springer, Heidelberg, 1981MATHCrossRefGoogle Scholar
  10. 10.
    Karlsson M., Pohjala P., Rantanen H. and Kalli S., Evaluation of Scanning Rate Up Conversion Algorithms; Subjective Testing of Interlaced to Progressive Conversion, IEEE Transactions on Consumer Electronics, Vol. 38, No. 3, pp. 162–167, 1992CrossRefGoogle Scholar
  11. 11.
    Kerre E., Introduction to the basic principles of fuzzy set theory and some of its applications, Communication & Cognition, Ghent, 1991Google Scholar
  12. 12.
    Koivunen T., A Noise-insensitive Motion Detector, IEEE Transactions on Consumer Electronics, Vol. 38, No. 3, pp. 168–173, 1992CrossRefGoogle Scholar
  13. 13.
    Kuo C.J., Liao C. and Lin C.C., Adaptive Interpolation Technique for Scanning Rate Conversion, IEEE Transactions on Circuits and Systems for Video Technology, Vol. 6, No. 3, pp. 317–321, 1996CrossRefGoogle Scholar
  14. 14.
    Larsen P.M., Industrial applications of fuzzy logic control, J. Man Mach. Studies, Vol. 12, No. 1, pp. 3–10, 1980CrossRefGoogle Scholar
  15. 15.
    Lee C.C., Fuzzy Logic in Control Systems: Fuzzy Logic Controller, IEEE Transactions on Systems, Man, and Cybernetics, Vol. 20, No. 2, pp. 404–435, 1990MATHCrossRefGoogle Scholar
  16. 16.
    Van Leekwijck W. and Kerre E., Defuzzification: criteria and classification, Fuzzy Sets and Systems, Vol. 108, pp. 159–178, 1999MathSciNetMATHCrossRefGoogle Scholar
  17. 17.
    Mamdani E.H. and Gaines B.R., “Fuzzy Reasoning and its Applications”, Academic, London, 1981MATHGoogle Scholar
  18. 18.
    Marsh D., TV and the PC, State of the Union, WinHEC 99 White Paper, Microsoft, 1999Google Scholar
  19. 19.
    Michaud F., Dinh C., Lachiver G., Fuzzy Detection of Edge-Direction for Video Line Doubling, IEEE Transactions on circuits and systems for video technology, Vol. 7, No. 3, pp. 539–542, 1997CrossRefGoogle Scholar
  20. 20.
    Poynton C.A., “A Technical Introduction to Digital Video”, Wiley, New York, 1996Google Scholar
  21. 21.
    Prodan R.S., Multidimensional digital signal processing for television scan conversion, Philips Journal of Research, Vol. 41, No. 6, pp. 576–603, 1986Google Scholar
  22. 22.
    Russo F., FIRE operators for image processing, Fuzzy Sets and Systems, Vol. 103, No. 2, pp. 265–275, 1999MathSciNetCrossRefGoogle Scholar
  23. 23.
    Takada S., Ohsawa M. et al., Video signal-processing technique for video printer, Sharp Technical Journal, No. 62, pp. 5–9, 1995Google Scholar
  24. 24.
    Tabatabai A., Jasinschi R. and Naveen T., Motion Estimation Methods for Video Compression — A Review, Journal of the Franklin Institute, Vol. 335B, No. 8, pp. 1411–1441, 1998CrossRefGoogle Scholar
  25. 25.
    Tekalp A.M., “Digital Video Processing”, Prentice Hall, New York, 1995Google Scholar
  26. 26.
    Thomas G.A., A comparison of motion-compensated interlace-to-progressive conversion methods, BBC Research and Development Report, No. 1996/9, 1996.Google Scholar
  27. 27.
    Tsang D., Bensaou B. and Lam S., Fuzzy-Based Rate Control for Real-Time MPEG Video, IEEE Transactions on Fuzzy Systems, Vol. 6, No. 4, pp. 504–516, 1998CrossRefGoogle Scholar
  28. 28.
    Van De Ville D., Rogge B., Philips W. and Lemahieu I., De-interlacing using fuzzy-based motion detection, in: “Proceedings of KES’99 — the Third International Conference on Knowledge-Based Intelligent Information Engineering Systems” (Adelaide, Australia), pp. 263–267, 1999Google Scholar
  29. 29.
    Van Someren N., “High Quality De-interlacing of Television Images”, PhD Thesis. Trinity College, University of Cambridge, 1994Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2000

Authors and Affiliations

  • Dimitri Van De Ville
    • 1
  • Wilfried Philips
    • 2
  • Ignace Lemahieu
    • 1
  1. 1.Department of Electronics and Information Systems (Elis)Ghent UniversityGentBelgium
  2. 2.Department for Telecommunication and Information Processing (Telin)Ghent UniversityGentBelgium

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