Abstract
Shape information is an important distribution to Content-Base Image Retrieval (CBIR) systems. There are two major types of shape descriptors, namely region-based and contour-based. In this paper we present a shape retrieval method that makes use of a contour-based descriptor, Principal Components Descriptor (PCD). In PCD, shapes are aligned on principal axes and described by a combination of the mean shape and weighted eigenvectors. The retrieval is achieved by comparing the weights of the eigenvectors. The developed approach is applied to Sharvit’s Silhouettes database and the results are compared with MPEG-7 standard contour-based descriptor, Curvature Scale Space (CSS). The comparison indicates that PCD shows higher accuracy than CSS.
This is a preview of subscription content, log in via an institution to check access.
Preview
Unable to display preview. Download preview PDF.
Similar content being viewed by others
References
Kauppinen, H., Seppannen, T., Pietikainen, M.: An experimental comparison of autoregressive and fourier-based descriptors in 2d shape classification. IEEE Trans. on Pattern Analysis and Machine Intelligence 17, 201–207 (1995)
Jaggi, S., Karl, W., Mallat, S., Willsky, A.: Silhouette recognition using highresolution pursuit. Pattern Recognition 32, 753–771 (1999)
Zahn, C., Roskies, R.: Fourier descriptor for plane closed curves. IEEE Trans. on Computers 21, 269–281 (1972)
Chuang, G.H., Kuo, C.C.: Wavelet descriptor of planar curves: theory and application. IEEE Trans. on Image Processing 5, 56–70 (1996)
Mokhtarian, F., Mackworth, A.: A theory of multiscale, curvature-baes shape representation for planar curves. IEEE Trans. on Pattern Analysis and Machine Intelligence 14, 789–805 (1992)
Mokhtarian, F., Abbasi, S., Kittler, J.: Robust and efficient shape indexing through curvature scale space. In: Proceedings of the British Machine Vision Conference, Edinburgh,UK, BMVA (1996)
Bangham, J.A., Hidalgo, J.R., Harvey, R., Cawley, G.: The segmentation of images via scale-space trees. In: Carter, J.N., Nixon, M.S. (eds.) BMVC, Southampton, British Machine Vision Association, pp. 33–43 (1998)
Carson, C., Belongie, S., Greenspan, H., Malik, J.: Blobworld: Image segmentation using expectation-maximization and its application to image querying. IEEE Transactions on Pattern Analysis and Machine Intelligence 24, 1026–1038 (2002)
Cootes, T., Taylor, C., Cooper, D., Graham, J.: Active shape models - their training and application. Computer Vision and Image Understanding 61, 38–59 (1995)
Sharvit, D., Chen, J., Tek, H., Kimia, B.: Symmetry-based indexing of image database. Journal of Vissual Communication and Image Representation 9, 366–380 (1998)
Müller, H., Müller, W., Squire, D., Marchand-Maillet, S., Pun, T.: Performance evaluation in content-based image retrieval: overview and proposals. In: Pattern Recognition Letters, vol. 22, pp. 593–601. Elsevier, Amsterdam (2001)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2005 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Wang, B., Bangham, A.J., Zhu, Y. (2005). Shape Retrieval by Principal Components Descriptor. In: Singh, S., Singh, M., Apte, C., Perner, P. (eds) Pattern Recognition and Image Analysis. ICAPR 2005. Lecture Notes in Computer Science, vol 3687. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11552499_69
Download citation
DOI: https://doi.org/10.1007/11552499_69
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-28833-6
Online ISBN: 978-3-540-31999-3
eBook Packages: Computer ScienceComputer Science (R0)