Abstract
A cognitively motivated similarity measure is presented and its properties are analyzed with respect to retrieval of similar objects in image databases of silhouettes of 2D objects. To reduce influence of digitization noise as well as segmentation errors the shapes are simplified by a novel process of digital curve evolution. To compute our similarity measure, we first establish the best possible correspondence of visual parts (without explicitly computing the visual parts). Then the similarity between corresponding parts is computed and aggregated. We applied our similarity measure to shape matching of object contours in various image databases and compared it to well-known approaches in the literature. The experimental results justify that our shape matching procedure gives an intuitive shape correspondence and is stable with respect to noise distortions.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
M. Arkin, L. P. Chew, D. P. Huttenlocher, K. Kedem, and J. S. B. Mitchell. An efficiently computable metric for comparing polygonal shapes. IEEE Trans. PAMI, 13: 209–206, 1991.
R. Basri, L. Costa, D. Geiger, and D. Jacobs. Determining the similarity of deformable shapes. In Proc. IEEE Workshop on Physics-Based Modeling in Computer Vision, pages 135–143, 1995.
R. Basri, L. Costa, D. Geiger, and D. Jacobs. Determining the similarity of deformable shapes. Vision Research, 38: 2365–2385, 1998.
A. Bengtsson and J.-O. Eklundh. Shape representation by mutliscale contour approximation. IEEE Trans. Pattern Analysis and Machine Intelligence, 13: 85–93, 1991.
J. Beusmans, D.D. Hoffman, and B.M. Bennett. Description of solid shape and its inference from occluding contours. Journal of the Optical Society of America, A. 4: 1155–1167, 1987.
A.M. Bruckstein, G. Shapiro, and C. Shaked. Evolutions of planer polygons. Int. J. of of Pattern Recognition and AI, 9: 991–1014, 1995.
A. Brunn, U. Weidner, and W. Förstner. Model-based 2d-shape recovery. In Proc. of 17. DAGM Conf. on Pattern Recognition (Mustererkennung), pages 260–268, Bielefeld, Springer-Verlag, Berlin, 1995.
H. Freeman. Shape description via the use of critical points. Pattern Recognition, 10: 159–166, 1978.
D. D. Hoffman and W. A. Richards. Parts of recognition. Cognition, 18: 65–96, 1984.
D. D. Hoffman and M. Singh. Salience of visual parts. Cognition, 63: 2978, 1997.
D. Huttenlocher, G. Klanderman, and W. Rucklidge. Comparing images using the Hausdorff distance. IEEE Trans. PAMI, 15: 850–863, 1993.
J. J. Koenderink and A. J. Doom. The shape of smooth objects and the way contours end. Perception, 11:129–137, 1981.
L. J. Latecki, R.-R. Ghadially, R. Lakämper, and U. Eckhardt. Continuity of the discrete curve evolution. In SPIE and SIAM Conf. on Vision Geometry VIII, volume 3811, pages 212–223, July 1999.
L. J. Latecki and R. Lakämper. Convexity rule for shape decomposition based on discrete contour evolution. Computer Vision and Image Understanding, 73: 441–454, 1999.
L. J. Latecki and R. Lakämper. Polygon evolution by vertex deletion. In M. Nielsen, P. Johansen, O.F. Olsen, and J. Weickert, editors, Scale-Space Theories in Computer Vision. Proc. of Int. Conf. on Scale-Space ’89, volume LNCS 1682, Corfu, Greece, September 1999.
L. J. Latecki, R. Lakämper, and U. Eckhardt http://www.math.unihamburg.de/home/lakaemper/shape.
F. Mokhtarian, S. Abbasi, and J. Kittler. Efficient and robust retrieval by shape content through curvature scale space. In A. W. M. Smeulders and R. Jain, editors, Image Databases and Multi-Media Search, pages 51–58. World Scientific Publishing, Singapore, 1997.
F. Mokhtarian and A. K. Mackworth. A theory of multiscale, curvature-based shape representation for planar curves. IEEE Trans. PAMI, 14: 789805, 1992.
H. Nishida. Matching and recognition of deformed closed contours based on structual transformation models. Pattern Recognition, 31: 1557–1571, 1998.
U. Ramer. An iterative procedure for the polygonal approximation of plane curves. Computer Graphics and Image Processing, 1: 244–256, 1972.
S. Sclaroff. Deformable prototypes for encoding shape categories in image databases. Pattern Recognition, 30: 627–641, 1997.
K. Siddiqi and B. B. Kimia. Parts of visual form: Computational aspects. IEEE Trans. PAMI, 17: 239–251, 1995.
K. Siddiqi, A. Shokoufandeh, S. J. Dickinson, and S. W. Zucker. Shock graphs and shape matching. Int. J. of Computer Vision, 35 (1): 13–32, 1999.
K. Siddiqi, K. J. Tresness, and B. B. Kimia. Parts of visual form: Psychophysical aspects. Perception, 25: 399–424, 1996.
N. Ueda and S. Suzuki. Learning visual models from shape contours using multiscale convex/concave structure matching. IEEE Trans. PAMI, 15: 337–352, 1993.
Y. Uesaka. A new fourier description applicable to open curves. Trans. on IECE Japan A (in Japanese), J67-A: 166–173, 1984.
J. Weickert. A review of nonlinear diffusion filtering. In B. M. ter Haar Romeny, L. Florack, J. Koenderink, and M. Viergever, editors, Scale-Space Theory in Computer Vision, pages 3–28. Springer, Berlin, 1997.
C. T. Zahn and R. Z. Roskies. Fourier descriptors for plane closed curves. IEEE Trans. on Computers, 21: 269–281, 1972.
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2001 Springer Science+Business Media Dordrecht
About this chapter
Cite this chapter
Latecki, L.J., Lakämper, R. (2001). Shape Description and Search for Similar Objects in Image Databases. In: Veltkamp, R.C., Burkhardt, H., Kriegel, HP. (eds) State-of-the-Art in Content-Based Image and Video Retrieval. Computational Imaging and Vision, vol 22. Springer, Dordrecht. https://doi.org/10.1007/978-94-015-9664-0_4
Download citation
DOI: https://doi.org/10.1007/978-94-015-9664-0_4
Publisher Name: Springer, Dordrecht
Print ISBN: 978-90-481-5863-8
Online ISBN: 978-94-015-9664-0
eBook Packages: Springer Book Archive