Rotation invariant texture classification by ridgelet transform and frequency-orientation space decomposition

Signal Processing

Volumn 88, Issue 1, 2008, Pages 189-199

  Pan, Wumo ^a   Bui, T D ^a   Suen, C Y ^a  

^a Gina Cody School of Engineering and Computer Science   (Canada)

Author keywords

B spline wavelet; Frequency orientation decomposition; Randon transform; Ridgelet transform; Rotation invariance; Texture classification

Indexed keywords

CONTENT BASED RETRIEVAL; NATURAL FREQUENCIES; THEOREM PROVING; WAVELET TRANSFORMS;

FREQUENCY ORIENTATION DECOMPOSITION; RANDON TRANSFORMS; RIDGELET TRANSFORMS; ROTATION INVARIANCE;

FEATURE EXTRACTION;

EID: 34548572914     PISSN: 01651684     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.sigpro.2007.07.019     Document Type: Article

References (34)

1. Kandaswamy U., Adjeroh D.A., and Lee M.C. Efficient texture analysis of SAR imagery. IEEE Trans. Geosci. Remote Sensing 43 9 (2005) 2075-2083
2. Busch A., Boles W.W., and Sridharan S. Texture for script identification. IEEE Trans. Pattern Anal. Mach. Intell. 27 11 (2005) 1720-1732
3. D. Chetverikov, J. Liang, J. Komuves, R.M. Haralick, Zone classification using texture features, in: Proceedings of the 13th International Conference on Pattern Recognition, vol. 3, 1996, pp. 676-680.
4. Liu Y., and Srihari S.N. Document image binarization based on texture features. IEEE Trans. Pattern Anal. Mach. Intell. 19 5 (1997) 540-544
5. Tan T.N. Rotation invariant texture features and their use in automatic script identification. IEEE Trans. Pattern Anal. Mach. Intell. 20 7 (1998) 751-756
6. Bleck J.S., Ranft U., Gebel M., Hecker H., Westhoff-Bleck M., Thiesemann C., Wagner S., and Manns M. Random field models in the textural analysis of ultrasonic images of the liver. IEEE Trans. Med. Imaging 15 6 (1996) 796-801
7. Flickner M., Sawhney H., Niblack W., Ashley J., Huang Q., Dom B., Gorkani M., Hafner J., Lee D., Petkovic D., Steele D., and Yanker P. Query by image and video content: the qbic system. IEEE Comput. 28 9 (1995) 23-32
8. Randen T., and Husoy J.H. Filtering for texture classification: a comparative study. IEEE Trans. Pattern Recognition Mach. Intell. 21 4 (1999) 291-310
9. Zhang J., and Tan T. Brief review of invariant texture analysis methods. Pattern Recognition 35 3 (2002) 735-747
10. Kashyap R.L., and Khotanzed A. A model-based method for rotation invariant texture classification. IEEE Trans. Pattern Anal. Mach. Intell. 8 4 (1986) 472-481
11. Cohen F.S., Fan Z., and Patel M.A. Classification of rotated and scaled textured images using Gaussian Markov random field models. IEEE Trans. Pattern Anal. Mach. Intell. 13 2 (1991) 192-202
12. Mao J., and Jain A.K. Texture classification and segmentation using multiresolution simultaneous autoregressive models. Pattern Recognition 25 2 (1992) 173-188
13. Campisi P., Neri A., Panci G., and Scarano G. Robust rotation-invariant texture classification using a model-based approach. IEEE Trans. Image Process. 13 6 (2004) 782-791
14. Kingsbury N.G. Complex wavelets for shift invariant analysis and filtering of signals. J. Appl. Comput. Harmonic Anal. ( 3) (2001) 234-253
15. Charalampidis D., and Kasparis T. Wavelet-based rotational invariant roughness features for texture classification and segmentation. IEEE Trans. Image Process. 11 8 (2002) 825-837
16. Do M.N., and Vetterli M. Rotation invariant characterization and retrieval using steerable wavelet-domain hidden Markov models. IEEE Trans. Multimedia 4 4 (2002) 517-526
17. Pun C.M., and Lee M.C. Log-polar wavelet energy signatures for rotation and scale invariant texture classification. IEEE Trans. Pattern Anal. Mach. Intell. 25 5 (2003) 590-603
18. Jafari-Khouzani K., and Soltanian-Zadeh H. Rotation invariant multiresolution texture analysis using radon and wavelet transforms. IEEE Trans. Image Process. 14 6 (2005) 783-795
19. Jafari-Khouzani K., and Soltanian-Zadeh H. Radon transform orientation estimation for rotation invariant texture analysis. IEEE Trans. Pattern Anal. Mach. Intell. 27 6 (2005) 1004-1008
20. De Valois R.L., and De Valois K.K. Spatial Vision (1988), Oxford University Press, Oxford
21. Marcelja S. Mathematical description of the responses of simple cortical cells. Optical Soc. Am. J. A 70 (1980)
22. S.R. Fountain, T.N. Tan, Extraction of noise robust invariant texture features via multichannel filtering, in: Proceedings of the ICIP, vol. 3, 1997, pp. 197-200.
23. Haley G.M., and Manjunath B.S. Rotation-invariant texture classification using a complete space-frequency model. IEEE Trans. Image Process. 8 20 (1999) 255-269
24. W.M. Pan, T.D. Bui, C.Y. Suen, Rotation-invariant Texture Classification using Steerable Gabor Filter Bank, Springer Lecture Notes in Computer Science, vol. 3656, Springer, Berlin, 2005, pp. 746-753.
25. Porter R., and Canagarajah N. Robust rotation-invariant texture classification: Wavelet, Gabor filter and GMRF based schemes. IEE Proc. Vision Image Signal Process. 144 3 (1997) 180-188
26. E.J. Candes, D.L. Donoho, Ridgelets: a key to higher-dimensional intermittency? Philos. Trans. R. Soc. London A. 357 (1760) (1999) 2495-2509.
27. Chen G.Y., Bui T.D., and Krzyzak A. Rotation invariant pattern recognition using ridgelet, wavelet cycle-spinning, and fourier features. Pattern Recognition 38 12 (2005) 2314-2322
28. Chen G.Y., Bui T.D., and Krzyzak A. Rotation invariant feature extraction using ridgelet and fourier transforms. Pattern Anal. Appl. 9 1 (2006) 83-93
29. K. Huang, S. Aviyente, Rotation invariant texture classification with ridgelet transform and fourier transform, in: Proceedings of the ICIP, 2006, pp. 2141-2144.
30. Arivazhagan S., Ganesan L., and Subash Kumar T.G. Texture classification using ridgelet transform. Pattern Recognition Lett. 27 16 (2006) 1875-1883
31. Teolis A. Computational Signal Processing with Wavelets (1998), Birkhauser, Barel
32. Herman G.T. Image Reconstruction from Projections: The Fundamentals of Computerized Tomography (1980), Academic Press, New York
33. Ojala T., Pietikainen M., and Maenpaa T. Multiresolution gray-scale and rotation invariant texture classification with local binary patterns. IEEE Trans. Pattern Anal. Mach. Intell. 24 7 (2002) 971-987
34. MIT Media Lab Vision Textures 〈http://vismod.www.media.mit.edu〉.