Multimedia Tools and Applications

, Volume 32, Issue 1, pp 29–48 | Cite as

An experimental study of alternative shape-based image retrieval techniques

  • Cyrus ShahabiEmail author
  • Maytham Safar


Besides traditional applications (e.g., CAD/CAM and Trademark registry), new multimedia applications such as structured video, animation, and MPEG-7 standard require the storage and management of well-defined objects. These object databases are then queried and searched for different purposes. A sample query might be “find all the scenes that contain a certain object.” Shape of an object is an important feature for image and multimedia similarity retrievals. Therefore, in this study we focus on shape-based object retrieval and conduct a comparison study on four of such techniques (i.e., Fourier descriptors, grid based, Delaunay triangulation, and our proposed MBC-based methods (e.g., MBC-TPVAS)). We measure the effectiveness of the similarity retrieval of the four different shape representation methods in terms of recall and precision. Our results show that the similarity retrieval accuracy of our method (MBC-TPVAS) is as good as that of the other methods, while it observes the lowest computation cost to generate the shape signatures of the objects. Moreover, it has low storage requirement, and a comparable computation cost to compute the similarity between two shape signatures. In addition, MBC-TPVAS requires no normalization of the objects, and is the only method that has direct support for S-RST query types. In this paper, we also propose a new shape description taxonomy.


Shape representation Shape similarity Similarity measure Image retrieval 


Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.


  1. 1.
    Agrawal R, Faloutsos C, Swami A (1993, October) Efficient similarity search in sequence databases. In: Proceedings of the international conference of FODO, Chicago, ILGoogle Scholar
  2. 2.
    Berchtold S, Keim D, Kriegel HP (1997) Using extended feature objects for partial similarity retrieval. In: Proceedings of 23rd very large databases (VLDB) conference. Springer, Berlin Heidelberg New York, pp 333–348Google Scholar
  3. 3.
    Eakins JP (1994) Retrieval of trade mark images by shape feature. In: Proceedings first international conference on electronic library and visual information system research, de Montfort University, Milton Keynes, UK, pp 101–109Google Scholar
  4. 4.
    Faloutsos C, Ranganathan M, Manolopoulos Y (1994) Fast subsequence matching in time–series databases. In: Proceedings of the ACM SIGMOD international conference on management of data, Minneapolis, MNGoogle Scholar
  5. 5.
    Gary J, Mehrotra R (1993) Feature-based retrieval of similar shapes. In: Proceedings of international conference on data engineering (ICDE), Vienna, Austria, pp 108–115Google Scholar
  6. 6.
    Gary J, Mehrotra R (1995) Similar-shape retrieval in shape data management. IEEE Comput Mag 28:57–62Google Scholar
  7. 7.
    Ghandeharizadeh S (1995) Stream-based versus structured video objects: issues, solutions, and challenges. In: Jajodia S, Subrahmanian V (eds) Multimedia DB systems: issues and res. direct. Springer, Berlin Heidelberg New YorkGoogle Scholar
  8. 8.
    Gonzalez RC, Wintz P (1987) Digital image processing 2nd edn. Addison-Wesley, Reading, MAGoogle Scholar
  9. 9.
    Granlund JH (1972) Fourier preprocessing for hand print character recognition. IEEE Trans Comput 21:195–201MathSciNetCrossRefzbMATHGoogle Scholar
  10. 10.
    Jagadish HV (1991) A retrieval technique for similarity shapes. In: Proceedings ACM SIGMOD international conference on management of data, Denver, CO, pp 208–217Google Scholar
  11. 11.
    Korn F, Sidiropoulos N, Faloutsos C, Siegel E, Protopapas Z (1996) Fast nearest neighbor search in medical image databases. In: Proceedings 22nd VLDB conference, Mumbai, India, pp 215–226Google Scholar
  12. 12.
    Lu G, Sajjanhar A (1999) Region-based shape representation and similarity measure suitable for content-based image retrieval. Multimedia Syst 7(2):165–174CrossRefGoogle Scholar
  13. 13.
    Mehtre BM, Kankanhalli MS, Lee WF (1997) Shape measures for content based image retrieval: a comparison. Inf Process Manag 33(3):319–337CrossRefGoogle Scholar
  14. 14.
    Mokhtarian F, Abbasi S, Kitter J (1996) Efficient and robust retrieval by shape content through curvature scale space. In: Proceedings of international workshop on image database and multimedia search, Amesterdam, Netherlands, pp 35–42Google Scholar
  15. 15.
    Pitas I (1993) Digital image processing algorithms. Prentice Hall, Englewood Cliffs, NJGoogle Scholar
  16. 16.
    Safar M, Shahabi C (1999) 2D topological and direction relations in the world of minimum bounding circles. In: Proceedings of IEEE international database engineering and applications symposium (IDEAS), Montreal, Canada, pp 239–247, 2–4 AugustGoogle Scholar
  17. 17.
    Safar M, Shahabi C, Tan, C-H (2000) Resiliency and robustness of alternative shape-based image retrieval techniques. In: Proceedings of IEEE international database engineering and applications symposium (IDEAS), Yokohama, JapanGoogle Scholar
  18. 18.
    Sajjanhar A, Lu G (1997a) Indexing 2D non-occluded shape for similarity retrieval. In: Proceedings of SPIE conference on applications of digital image processing XX, vol 3164, San Diego, CA, pp 188–197, 30 July–1 AugustGoogle Scholar
  19. 19.
    Sajjanhar A, Lu G (1997b) A grid based shape indexing and retrieval method. Aust Comput J 29(4):131–140Google Scholar
  20. 20.
    Sajjanhar A, Lu G (1998) A comparison of techniques for shape retrieval. In: International conference on computational intelligence and multimedia applications, Monash University, Gippsland Campus, Australia, pp 854–859, 9–11 FebruaryGoogle Scholar
  21. 21.
    Sajjanhar A, Lu G, Wright J (1997) An experimental study of moment invariants and Fourier descriptors for shape based image retrieval. In: Proceedings of the second Australia document computing symposium, Melbourne, Australia, pp 46–54, 5 AprilGoogle Scholar
  22. 22.
    Shahabi C, Safar M (1999) Efficient retrieval and spatial querying of 2D objects. In: Proceedings of IEEE international conference on multimedia computing and systems (ICMCS), Florence, Italy, pp 611–617, 7–11 JuneGoogle Scholar
  23. 23.
    Sul C, Lee K, Wohn K (1998) Virtual stage: a location-based karaoke system. IEEE Multimed 5:42–52CrossRefGoogle Scholar
  24. 24.
    Tao Y, Grosky WI (1999, January) Delaunay triangulation for image object indexing: a novel method for shape representation. In: Proceedings of the 7th SPIE symposium on storage and retrieval for image and video databases, San Jose, CA, pp 631–642Google Scholar
  25. 25.
    Tao Y, Grosky WI (1999, January) Object-based image retrieval using point feature maps. In: Proceedings of the international conference on database semantics (DS-8), Rotorua, New Zealand, pp 59–73Google Scholar

Copyright information

© Springer Science+Business Media, LLC 2006

Authors and Affiliations

  1. 1.Integrated Media Systems Center, Department of Computer ScienceUniversity of Southern CaliforniaLos AngelesUSA
  2. 2.Computer Engineering DepartmentKuwait UniversityKuwaitKuwait

Personalised recommendations