Abstract
A novel approach to 2D shape representation which is invariant to the rotation is introduced. The proposed system determines how any given shape should be rotated depending on the principal axis of the image. After rotation, a space-filling curve is applied to obtain a 1D vector representation of the image. This vector is later compressed in order to obtain a very small 1D vector that adequately represents an image – this is called the Shape Feature Vector (SFV). The system can import these SFVs into a database and perform retrieval queries for the best possible match to a query image. The SFV of a query image is obtained and the euclidean distance measure is used to determine a best match. Three different space-filling curves, Hilbert, Moore, and Z-order, are compared through the recognition rate results. Results from testing have shown significant improvement over previous shape representation methods using the Hilbert curve in the case of similar shapes with different initial orientations while not sacrificing precision in cases where the orientation is similar. Additionally, it was found that all three space-filling curves performed similarly.
This is a preview of subscription content, log in via an institution.
Buying options
Tax calculation will be finalised at checkout
Purchases are for personal use only
Learn about institutional subscriptionsPreview
Unable to display preview. Download preview PDF.
References
Belongie, S., Malik, J., Puzicha, J.: Shape matching and object recognition using shape contexts. IEEE Transactions on Pattern Analysis and Machine Intelligence, 509–522 (2002)
Berretti, S., Del Bimbo, A., Pala, P.: Retrieval by Shape Similarity with Perceptual Distance and Effective Indexing. IEEE Transactions on Multimedia, 225–239 (2000)
Bartolini, I., Ciaccia, P., Patella, M.: WARP – Accurate retrieval of shapes using phase of Fourier descriptors and time warping distance. IEEE Transactions on Pattern Analysis and Machine Intelligence, 142–147 (2005)
Lu, G.J., Sajjanhar, A.: Region-based shape representation and similarity measure suitable for content-based image retrieval. Multimedia Syst. 7(2), 165–174 (1999)
Kim, W.-Y., Kim, Y.-S.: A region-based shape descriptor using Zernike moments. Signal Processing: Image Communication 16(1-2), 95–102 (2000)
Gorelick, L., Galun, M., Sharon, E., Basri, R., Brandt, A.: Shape Representation and Classification using the Poisson Equation. In: 2004 IEEE Conference on Computer Vision and Pattern Recognition, vol. 2, pp. 61–67. IEEE Press, New York (2004)
Ebrahim, Y., Ahmed, M., Chau, S.C., Abdelsalem, W.: Shape Representation and Description Using the Hilbert Curve. Pattern Recognition Letters 30(4), 348–358 (2008)
Ebrahim, Y., Ahmed, M., Chau, S.-C., Abdelsalam, W.: A View-Based 3D Object Shape Representation Technique. In: Kamel, M.S., Campilho, A. (eds.) ICIAR 2007. LNCS, vol. 4633, pp. 411–422. Springer, Heidelberg (2007)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2009 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Armstrong, J., Ahmed, M., Chau, SC. (2009). A Rotation-Invariant Approach to 2D Shape Representation Using the Hilbert Curve. In: Kamel, M., Campilho, A. (eds) Image Analysis and Recognition. ICIAR 2009. Lecture Notes in Computer Science, vol 5627. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-02611-9_59
Download citation
DOI: https://doi.org/10.1007/978-3-642-02611-9_59
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-02610-2
Online ISBN: 978-3-642-02611-9
eBook Packages: Computer ScienceComputer Science (R0)