Skip to main content
Log in

Shape representation and coding of visual objets in multimedia applications — An overview

Revue des MÉthodes de ReprÉsentation et de Codage de Formes D’objets Visuels dans les Applications MultimÉdia

  • Published:
Annales Des Télécommunications Aims and scope Submit manuscript

Abstract

Emerging multimedia applications have created the need for new functionalities in digital communications. Whereas existing compression standards only deal with the audio-visual scene at a frame level, it is now necessary to handle individual objects separately, thus allowing scalable transmission as well as interactive scene recomposition by the receiver. The future MPEG-4 standard aims at providing compression tools addressing these functionalities. Unlike existing frame-based standards, the corresponding coding schemes need to encode shape information explicitly. This paper reviews existing solutions to the problem of shape representation and coding. Region and contour coding techniques are presented and their performance is discussed, considering coding efficiency and rate-distortion control capability, as well as flexibility to application requirements such as progressive transmission, low-delay coding, and error robustness.

Résumé

Les besoins en matière de fonctionalité orientées objet dans les communications audioviduelles sont apparus récemment avec l’émergence d’application nouvelles telles que la video conférence, les vidéophones et la vidéo interactive. Alors que les normes de compression existantes traitent la scène audio-visuelle au niveau de la trame, il est maintenant nécessaire de traiter séparément les différents objet présents, permettant ainsi une transmission échelonnable aussi bien que la recomposition de la scène par le receveur. La future norme MPEG-4 a pour but de proposer des outils de compression offrant ces nouvelles fonctionalités. Contrairement aux standards orientés trame existants, les schémas de codage correspondants doivent intégrer l’information de forme. Cet article présente un certain nombre de solutions existantes au problème de la représentation et du codage des formes. Différentes techniques de codage deformes et de contours sont présentées et leurs performances sont analysées en considérant l’efficacité du codage et la capacité de régulation débit/distortion, ainsi que la flexibilité vis-à-vis des besoins de l’application, tels que la transmission progressive, le codage à court délai, et la résistance aux erreurs.

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

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Similar content being viewed by others

References

  1. Ansari (N.), Delp. (E. J.), On detecting dominant points.Pattern Recognition, 24:441–450, (1991).

    Article  Google Scholar 

  2. Ayer (S.), Sequential and competive methods for estimation of multiple motions.PhD thesis, EPFL, Lausanne, Switzerland, (1995).

  3. Ballard (D.), Brown (C.), Computer vision.Prentice Hall, 1982.

  4. Bossen (F.). Ebrahimi (T.), Region shape coding.Technical Report M0318, ISO/IECJTCl /SC29 /WG11, (Nov. 1995).

  5. Bossen (F.), Ebrahimi (T.). A simple efficient binary shape coding technique based on bitmap representation.Int. Conf. on Acoustics, speech and signal processing, (1997).

  6. Brady (N.), Bossen (F.), Murphy (N.) Context-based arithmetic encoding of 2D shapes sequences.Int. Conf. on Image Processing, (1997).

  7. Brady (N.), Ducla-Soares (L.). Error resilience of arbitrarily shape vos (ce el4).Technical Report M2370, ISO / IEC JTC1 / SC29 /WG11, (July 1997).

  8. Brigger (P.). Morphological shape representation using the skeleton decomposition : application to image coding.PhD thesis, EPFL, Lausanne, Switzerland, (1995).

  9. Brigger (P.), Kunt (M.). Morphological contour coding using distance functions optimized by genetic algorithms.Int. Conf. on Image Processing, volume I, pp. 534–537, (Nov. 1995).

    Google Scholar 

  10. LE Buhan (C), Reusens (E.), Ebrahimi (T.). Object-scalable dynamic coding of visual information.Proc. EUSIPCO. (Sept 1996).

  11. Cleary (J.), Witten (I.). Data compression using adaptive coding and partial string matching.IEEE Trans. COM-32(4), (Apr. 1984).

  12. Berlin (HHI) COST211ter. Segmentation based coding scheme for object scalable and quality scalable coding of video.Technical Report M0415, ISO/IEC JTC1 /WG11, (Nov. 1995).

  13. Duda (R. D.), Hart (P. E.). Pattern classification and scene analysis.Wiley, New York, (1973).

    MATH  Google Scholar 

  14. Dunham (J.). Optimum uniform piecewise linear approximation of planar curves.IEEE Trans. PAM1,8(l):67–75, (Jan. 1986).

    Google Scholar 

  15. Eden (M.), Kocher (M.). On the performance of a contour coding algorithm in the context of image coding Part I: contour segment coding.Signal Processing,8:381–386, (1985).

    Article  Google Scholar 

  16. Etoh (M.), Boon (C.S.), andKadono (S.). Template-based video coding with opacity representation.IEEETrans. CSVT.,7(l):172–180, (Feb. 1997).

    Google Scholar 

  17. Foley (J. D.), Dam (A.van), Feiner (S. K.), Hughes (J. F). Computer graphics : principles and practice.Adision-Wesley, 2nd edition, (1990).

  18. Freeman (H.). On the encoding of arbitrary geometric configurations.IRE Trans. EC-10: 260–268, (June 1961).

    MathSciNet  Google Scholar 

  19. Freeman (H.) Computer processing of line drawing images.Computing Surveys,6: 57–97, (March 1974).

    Article  MATH  Google Scholar 

  20. Gerken (P.). Object-based analysis-synthesis coding of image sequences at very low bit rates.IEEE Trans. CSVT,4(3):-235, (1994).

    Google Scholar 

  21. Gu (C.). Multivalued morphology and segmentation-based coding.PhD thesis, EPFL, Lausanne, Switzerland, (1996).

  22. Gu (C.), Kunt (M.). Contour simplification by a new nonlinear filter region-based coding.IEEE International Conference on Image Processing, Los Alamitos, volume 3, pp. 751–755, (1994).

    Google Scholar 

  23. *** Ad hoc group on MPEG-4 video VM editing. MPEG-4 video verification model version 2.0.Technical Report JTCl / SC29/WG11 /N1260, ISO/IEC, (March 1996).

  24. *** Ad hoc group on shape coding. Description of core experiments on shape coding.Technical Report JTCl / SC29 / WG11 / M0889, ISO / IEC, (May 1996).

  25. *** Recommendation T. 6.Facsimile coding schemes and coding control functions for Group 4 facsimile apparatus ITU-T.

  26. *** Recommendation T. 82.Information technology - coded representation of picture and audio information - progressive bilevel image compression ITU-T.

  27. Kaneko (T.), Okudaira (M). Encoding of arbitrary curves based on chain code representation.lEEETrans. COM.,33(7): 697–707, (July 1985).

    Article  Google Scholar 

  28. Kunt (M.), Ikonomopoulos (A.), Kocher (M.). Second generation image coding techniquesProc. IEEE,73, (4): 549–575, (1985.)

    Article  Google Scholar 

  29. Langdon (G.), Rissanen (J.). Compression of black-white images with arithmetic coding.IEEE Trans. COM,29(6): 858–867, (June 1981).

    Article  Google Scholar 

  30. Li (H.), Gerken (P.). Comparison of different error criteria for shape coding.Technical Report M0697, ISO / IEC JTCl / SC29/ WG11, (March 1996).

  31. Loncaric (S.), Dhawan (A.). Near-optimal MST-based shape description using genetic algorithm.Pattern Recognition,28(4):571–579,(Apr. 1995).

    Article  Google Scholar 

  32. Lu (C.) andDunham (J.). Highly efficient coding schemes for contour lines based on chain code representations.IEEE Trans. COM,39(10): 1511–1514, (Oct. 1991).

    Article  Google Scholar 

  33. Maragos (P. A.), Schafer (R. W.). Morphological skeleton and coding of binary images.IEEE Trans ASSP34(5): 1228–1244, (Oct. 1986);

    Article  Google Scholar 

  34. Mehrotra (R.), Gary (J. E.). Similar shape retrieval in shape data management.Computer,28(9): 57–62, (1995).

    Article  Google Scholar 

  35. Moccagatta (I.), Schutz (M.), Moscheni (F.), Dufaux (F.). Vector quantization (VQ)-based motion field refinement technique for image sequence coding.Proc. SPIE - The International Society for Optical Engineering, volume 2451, pp. 156–167. Society of Photo-Optical Instrumentation Engineers. Bellingham (1995).

    Google Scholar 

  36. *** MPEG. Video verification model version 7.0.Technical Report Available from http : // drogo.cselt.stet.it / mpeg, ISO / IECJTC1/SC29/WG11, (1997).

  37. Ramer (U.). An iterative procedure for polygonal approximation of plane curves.Computer Graphics and Image Processing,1: 244–256, (1972).

    Article  Google Scholar 

  38. Ray (B.), Ray (K.). A new split-and-merge for polygonal approximation of chain coded curves.Pattern Recognition Letters,16: 161–169, (Feb. 1995).

    Article  Google Scholar 

  39. Ray (B.), Ray (K.). An optimal algorithm for polygonal approximation of digitized curves using 1. 1 norm.Pattern Recognition,26: 505–509, (Feb. 1995).

    Google Scholar 

  40. Rissanen (J.). Generalized Kraft inequality and arithmetic coding.IBM Journal Res. and Dev.,20: 198–203, (May 1976).

    Article  MATH  MathSciNet  Google Scholar 

  41. Rosenfeld (A.), Kak (A. C). Digital picture processing, volume 2.Academic Press, New York, USA, 2nd edition, (1982).

    Google Scholar 

  42. Salembier (P.), Marqués (F.), Gasull (A.). Coding of partition sequences.In L. Torres and M. Kunt, editors,Video coding. Kluwer Academic, (1996).

  43. Shapiro (L.), MacDonald (R.), Sternberg (S.). Ordered structural shape matching with primitive extraction by mathematical morphology.Pattern Recognition,20: 75–90, (1987).

    Article  Google Scholar 

  44. Stuhlmuller(K. W.), Salai (A.), Girod (B.). Rate constrained contour representation for region-based motion compensation.Proc. Symp. on Visual Comm. and image Proc, SPIE, volume 2727, (March 1996).

  45. Written (I.), NeaI (R.), Cleary (J.). Arithmetic coding for data compression.Communications ACM,30 (6): 520–540, (June 1997).

    Article  Google Scholar 

  46. Yamaguchi (N.), Ida (T.), Watanabe (T.). A binary shape coding method using modified MMR.Int. Conf. on Image Processing, (Oct 1997).

Download references

Author information

Authors and Affiliations

Authors

Rights and permissions

Reprints and permissions

About this article

Cite this article

Jordan, C.L.B., Bhattacharjee, S., Bossen, F. et al. Shape representation and coding of visual objets in multimedia applications — An overview. Ann. Télécommun. 53, 164–178 (1998). https://doi.org/10.1007/BF02997675

Download citation

  • Received:

  • Issue Date:

  • DOI: https://doi.org/10.1007/BF02997675

Key words

Mots clés

Navigation