Abstract
Object shape is an important feature of images and is used in content-based image retrieval. Two important issues of shape based image retrieval are how to find a shape representation which is invariant to translation, scale and rotation, and a similarity measure which conforms with human perception. The purpose of this paper is to present a shape representation and similarity measure which meet these requirements.
We first describe a normalization process to obtain the unique chain code for each shape which is invariant to translation, scale and rotation. The unique chain code is suitable for shape representation but it is difficult to calculate shape similarity based shape chain codes. We then derive an alternative shape representation based on which shape similarity can be computed easily. Experiments show that the proposed shape representation and similarity measure compare favourable with the Fourier descriptor-based method in both retrieval effectiveness and efficiency.
This is a preview of subscription content, log in via an institution to check access.
Preview
Unable to display preview. Download preview PDF.
References
Jain, R. (ed.), “NSF Workshop on Visual Information Management Systems: Workshop Report”, Proceedings of the Conference on Storage and Retrieval for image and Video Databases, SPIE Proceedings Series, Vol. 1908, 1993, pp. 198–218.
Jain, R., Pentland, A. P. and Petkovic, D., “Workshop report: NSF-ARPA Workshop on Visual Information Management Systems”, June 1995, URL: http:// vision.ucsd.edu/papers/ VimsReport95. html.
Lu, G., Communication and Computing for Distributed Multimedia Systems, Artech House, 1996.
Chua T S et al, “A concept-based image retrieval system”, Proceedings of 27th Annual Hawaii International Conference on System Sciences, 4–7 January, 1994, pp.590–598.
Niblack W et al,'QBIC Project: querying images by content, using colour, texture, and shape', Storage and Retrieval for image and Video Databases, SPIE Proceedings Series, Vol. 1908, 1993, pp. 173–187.
Wu, J. K., et al, “STAR — A multimedia database system for trademark registration”. Proceedings of First International Conference, ADB-94, Vadstena, Sweden, June 21–23, 1994, pp. 109–122.
Lam, C. P, Wu, J.K., and Mehtre, B., “STAR — a system for trademark archival and retrieval”, Second Asian Conference on Computer Vision, December 5–8, Singapore, pp. III-214–217
Jain, A. K and Vailaya, A., “Image retrieval using color and shape”, Second Asian Conference on Computer Vision, December 5–8, Singapore, pp. II-529–II-533.
Gonzalez, R.C. and Wintz, P., Digital Image Processing, 2nd edition, Addison-Wesley, 1987.
Pitas, I., Digital Image Processing Algorithms, Prentice Hall, 1993.
Mohamad, D., Sulong, G. and Ipson, S. S., “Trademark matching using invariant moments”, Second Asian Conference on Computer Vision, December 5–8, Singapore, pp. I-439–I-444.
Cortelazzo, G. et al., “Trademark shapes description by string-matching techniques”, Pattern Recognition, Vol.27, No.8, pp. 1005–1018, 1994.
Mehrotra, R. and Gary, J. E, “Similar-shape retrieval in shape data management”, Computer, September 1995, pp. 57–62.
Jagadish, H. V, “A retrieval technique for similar shapes”, Proceedings of ACM SIGMOD, Colorado, May 1991, pp.208–217.
Kauppinen, H., Seppanen, T. and Pietikainen, M., “An experimental comparison of autoregressive and Fourier-based descriptors in 2D shape classification”, IEEE Transactions on PAMI, vol. 17, no. 2, Feb. 1995, pp. 201–207.
Sajjanhar, A. et al, “An experimental study of moment invariants and Fourier descriptor for shape based image retrieval”, Technical report, Gippsland School of Computing and Information Technology, Monash University, 1996. (Copies of the report can be obtained from Atul Sajjanhar on atuls@fcit.monash.edu.au)
Scassellati, B. et al, “Retrieving images by 2D shape: a comparison of computation methods with human perceptual judgements”, Storage and Retrieval for image and Video Databases II, 7–8 Feb. 1994, San Jose, California, USA, SPIE Proceedings Series, Vol. 2185, pp.2–14.
Frakes, W. B. and Baeza-Yates. R. (ed.), Information Retrieval: Data Structures and Algorithms, Prentice Hall, 1992.
Salton, G. and McGill, M. J., Introduction to Modern Information Retrieval, McGraw-Hill Book Company, 1983.
Lu, G. and Sajjanhar, A., “Region-Based Shape Representation and Similarity Measure Suitable For Content Based Image Retrieval”, Technical report, Gippsland School of Computing and Information Technology, Monash University 1996. (A copy of the report can be obtained from Atul Sajjanhar on atuls@fcit.monash.edu.au)
Author information
Authors and Affiliations
Editor information
Rights and permissions
Copyright information
© 1997 Springer-Verlag Berlin Heidelberg
About this chapter
Cite this chapter
Lu, G. (1997). Chain code-based shape representation and similarity measure. In: Leung, C. (eds) Visual Information Systems. Lecture Notes in Computer Science, vol 1306. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-63636-6_8
Download citation
DOI: https://doi.org/10.1007/3-540-63636-6_8
Published:
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-63636-6
Online ISBN: 978-3-540-69621-6
eBook Packages: Springer Book Archive