Abstract
A rotation invariant texture classification algorithm based on dual-tree complex wavelet transform (DT-CWT) and support vector machines (SVM) is proposed. First, the texture image is transformed by Radon transform to convert the rotation to translation, the rotation invariant feature vector is composed of the energies of the subbands acquired by DT-CWT which is shift invariant to the transformed texture image, the SVM algorithm is used to the texture classification at last. This algorithm is compared with the classifier of probabilistic neural network (PNN) and other rotation invariant texture classification algorithm, the experiment results show that it can improve the classification rate effectively.
This work is supported by Hebei education bureau under Grant 2004124.
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.
References
Selesnick, I.W., Baraniuk, R.G., Kingsbury, N.G.: The Dual-Tree Complex Wavelet Transform. IEEE Signal Processing 22(6), 123–151 (2005)
Burges, C.J.C.: A Tutorial on Support Vector Machines for Pattern Recognition. Data Mining and Knowledge Discovery 2(2), 1–47 (1998)
Kourosh, J.K., Hamid, S.Z.: Rotation-Invariant Multiresolution Texture Analysis Using Radon and Wavelet Transforms. IEEE Transactions on Image Processing 14(6), 783–795 (2005)
Specht, D.F.: Probabilistic Neural Networks. Neural Networks 3(1), 109–118 (1990)
Duan, R., Man, H., Chen, L.: Rotation Invariant Texture Classification Based on A Directional Filter Bank. In: IEEE International Conference on Multimedia and Expo (ICME’04), vol. 2, pp. 1291–1294 (2004)
Hill, P.R., Bull, D.R., Canagarajah, C.N.: Rotationally Invariant Texture Classification. In: IEE Seminar on Time-scale and Time-Frequency Analysis and Applications, vol. 20, pp. 1–5 (2000)
Author information
Authors and Affiliations
Editor information
Rights and permissions
Copyright information
© 2007 Springer Berlin Heidelberg
About this paper
Cite this paper
Chen, S., Shang, Y., Mao, B., Lian, Q. (2007). Rotation Invariant Texture Classification Algorithm Based on DT-CWT and SVM . In: Liu, D., Fei, S., Hou, Z., Zhang, H., Sun, C. (eds) Advances in Neural Networks – ISNN 2007. ISNN 2007. Lecture Notes in Computer Science, vol 4493. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-72395-0_58
Download citation
DOI: https://doi.org/10.1007/978-3-540-72395-0_58
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-72394-3
Online ISBN: 978-3-540-72395-0
eBook Packages: Computer ScienceComputer Science (R0)