Abstract
In this paper, an invariant algorithm for object recognition is proposed by using the Radon and Fourier transforms. It has been shown that this algorithm is invariant to the translation and rotation of pattern images. The scaling invariance can be achieved by the standard normalization techniques. Our algorithm works even when the center of the pattern object is not aligned well. This advantage is because the Fourier spectra are invariant to spatial shift in the radial direction whereas existing methods assume the centroids are aligned exactly. Experimental results show that the proposed method is better than the Zernike’s moments, the dual-tree complex wavelet (DTCWT) moments, and the auto-correlation wavelet moments for one aircraft database and one shape database.
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
Prokop, R.J., Reeves, A.P.: A survey of moments-based techniques for unoccluded object representation and recognition. CVGIP: Graphical Models Image Processing 54(5), 438–460 (1992)
Hu, M.K.: Visual pattern recognition by moment invariants. IRE Transactions on Information Theory 8, 179–187 (1962)
Khotanzad, A., Hong, Y.H.: Invariant image recognition by Zernike moments. IEEE Transactions on Pattern Analysis and Machine Intelligence 12(5), 489–497 (1990)
Chen, G.Y., Xie, W.F.: Wavelet-based moment invariants for pattern recognition. Optical Engineering 50(7), 077205 (2011)
Chen, G.Y., Bhattacharya, P.: Invariant pattern recognition using ridgelet packets and the Fourier transform. International Journal of Wavelets, Multiresolution and Information Processing 7(2), 215–228 (2009)
Hassanieh, H., Indyk, P., Katabi, D., Price, E.: Simple and Practical Algorithm for Sparse Fourier Transform. In: SODA (January 2012)
Hassanieh, H., Indyk, P., Katabi, D., Price, E.: Nearly Optimal Sparse Fourier Transform. In: STOC (May 2012)
Wang, X., Xiao, B., Ma, J.F., Bi, X.L.: Scaling and rotation invariant analysis approach to object recognition based on Radon and Fourier-Mellin transforms. Pattern Recognition 40, 3503–3508 (2007)
Sebastian, T.B., Klein, P.N., Kimia, B.B.: Recognition of Shapes by Editing Shock Graphs. In: International Conference on Computer Vision, ICCV (2001)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2013 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Chen, G., Bui, T.D., Krzyzak, A., Zhao, Y. (2013). Invariant Object Recognition Using Radon and Fourier Transforms. In: Guo, C., Hou, ZG., Zeng, Z. (eds) Advances in Neural Networks – ISNN 2013. ISNN 2013. Lecture Notes in Computer Science, vol 7951. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-39065-4_78
Download citation
DOI: https://doi.org/10.1007/978-3-642-39065-4_78
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-39064-7
Online ISBN: 978-3-642-39065-4
eBook Packages: Computer ScienceComputer Science (R0)