Abstract
In this paper, new wavelet-based affine invariant functions for shape representation are derived. These functions are computed from the wavelet approximation coefficients of the shape boundary. The first function is computed from applying a single wavelet transform, whereas the second function is computed from applying two different wavelet transforms. All the previously derived affine invariant functions were based on wavelet details coefficients which are sensitive to noise in the finer scale levels. The proposed invariant functions are more stable and less sensitive to noise than the details-based invariant functions.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
Similar content being viewed by others
References
Alferez, R., Wang, Y.: Geometric and illumination invariants for object recognition. IEEE Transactions on Pattern Analysis and Machine Intelligence 21(6), 505–536 (1999)
Costa, L., Cesar Jr., R.: Shape Analysis and Classification, Theory and Practice. CRC Press LLC, Boca Raton (2001)
Khalil, M., Bayoumi, M.: Affine invariant object recogniton using dyadic wavelet transform. In: 2000 Canadian Conference on Electrical and Computer Engineering, vol. 1, pp. 421–425 (2000)
Khalil, M., Bayoumi, M.: A dyadicw avelet affine invariant function for 2-D shape recognition. IEEE Transaction on Pattern Recognition and Machine Intelligence 23(10), 1152–1164 (2001)
Khalil, M., Bayoumi, M.: Affine invariants for object recognition using the wavelet transform. Pattern Recognition Letters 23, 57–72 (2002)
Mallat, S.: A Wavelet tour of signal processing, 2nd edn. Academic Press, London (1999)
Otterloo, P.: A contour-Oriented Approach to Shape Analysis. Printice Hall Int., Englewood Cliffs (1991)
Reiss, T.: Recognizing Planar Objects Using Invariant Image Features. Springer, Heidelberg (1991)
Sonka, M., Hlavac, V., Boyle, R.: Image Processing Analysis and Machine Vision. PWS Publishing (1999)
Tieng, Q., Boles, W.: Complex daubechies wavelet based affine invariant representation for object recognition. In: IEEE International Conference, Image Processing, vol. 1, pp. 198–202 (1994)
Tieng, Q., Boles, W.: Object recognition using an affine invariant wavelet representation. In: Proceedings of the 1994 Second Australian and New Zealand Conference on Intelligent Information Systems, pp. 307–311 (1994)
Tieng, Q., Boles, W.: An application of wavelet based affine invariant representation. Pattern Recognition Letters 16, 1287–1296 (1995)
Tieng, Q., Boles, W.: Wavelet based affine invariant representation: a tool for recognising planar objects in 3-D space. IEEE Trans. Pattern Analysis and Machine Intelligence 19(8), 846–857 (1997)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2003 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
El Rube, I., Ahmed, M., Kamel, M. (2003). New Wavelet-Based Invariant Shape Representation Functions. In: Perales, F.J., Campilho, A.J.C., de la Blanca, N.P., Sanfeliu, A. (eds) Pattern Recognition and Image Analysis. IbPRIA 2003. Lecture Notes in Computer Science, vol 2652. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-44871-6_26
Download citation
DOI: https://doi.org/10.1007/978-3-540-44871-6_26
Published:
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-40217-6
Online ISBN: 978-3-540-44871-6
eBook Packages: Springer Book Archive