Tytuł artykułu
Wybrane pełne teksty z tego czasopisma
Identyfikatory
Warianty tytułu
Języki publikacji
Abstrakty
The developments of multiresolution analysis, such as the wavelet, curvelet and contourlet transforms, have yielded adequate tools to characterize different scales of textures effectively. These methods exhibit different performances in processing texture images due to their different characteristics. In order to use those complementary characteristics simultaneously, a texture classification method by combining different image decomposition methods is proposed. The proposed method is compared with the methods where only one kind of multiresolution transform is used. The experimental results demonstrate that the combined features can effectively capture the complementary information from different image decomposition methods and obviously improve the texture classification accuracy.
Czasopismo
Rocznik
Tom
Strony
305--319
Opis fizyczny
Bibliogr. 29 poz., il., wykr.
Bibliografia
- [1] Haralick R.M., Shanmugam K., Dinstein I.: Textural features for image classification. IEEE Trans. SM&C, 3(6), 610-621, 1973.
- [2] Davis L.S.: Image texture analysis techniques - a survey, in: Digital Image Processing, Simon and R. M. Haralick Ed, 189-201, 1981.
- [3] Pietik Wanien M., Rosenfeld A., Davis L.S.: Experiments with texture classification using averages of local pattern matches. IEEE Trans. SM&C, 13(3), 421-426, 1983.
- [4] Chellappa R., Chatterjee S.: Classification of textures using Gaussian Markov random fields. IEEE Trans. ASSP, 33(4), 959-963, 1985.
- [5] Kashyap R.L., Khotanzed A.: A model based method for rotation invariant texture classification. IEEE Trans. PAMI, 8(4), 472-481, 1986.
- [6] Bovik A.C., Clarke M., Geisler W.S.: Multichannel texture analysis using localized spatial filters. IEEE Trans. PAMI, 12(1), 55-73, 1990.
- [7] Jain A.K., Farrokhnia F.: Unsupervised texture segmentation using Gabor filters. PR, 24(12), 1167- 1186, 1991.
- [8] Mao J., Jain A.K.: Texture classification and segmentation using multiresolution simultaneous autoregressive models. PR, 25(2), 173-188, 1992.
- [9] Laine A., Fan J.: Texture classification by wavelet packet signatures. IEEE Trans. PAMI, 15(11), 1186-1191, 1993.
- [10] Strand J., Taxt T.: Local frequency features for texture classification. PR, 27(10), 1397-1406, 1994.
- [11] Unser M.: Texture classification and segmentation using wavelet frames. IEEE Trans. IP, 4(11), 1549-1560, 1995.
- [12] Vapnik V.: Statistical Learning Theory. Wiley, New York, 1998.
- [13] Wang L., Liu J.: Texture classification using multiresolution Markov random field models. PRL, 20(2), 171-182, 1999.
- [14] Hatipoglu S., Mitra S.K., Kingsbury N.: Texture classification using dual-tree complex wavelet transform. Proc. 7th ICIPA, pp. 344-347, 1999.
- [15] Idrissa M., Acheroy M.: Texture classification using Gabor filters. PRL, 23(9), 1095-1102, 2002.
- [16] Arivazhagan S., Ganesan L.: Texture classification using wavelet transform. PRL, 24(9-10), 1513- 1521, 2003.
- [17] Do M.N.,Vetterli M.: The finite ridgelet transform for image representation. IEEE Trans. IP. 12(1), 16-28, 2003.
- [18] Li S.T., Kwok J.T., Zhu H.L., Wang Y.N.: Texture classification using the support vector machines. PR, 36(12), 2883-2893, 2003.
- [19] Zhang D., Chen Y.Q.: Artificial life: a new approach to texture classification. IJPR&AI, 19(2), 355-374, 2005.
- [20] Do M.N., Vetterli M.: The contourlet transform: An efficient directional multiresolution image representation. IEEE Trans. IP, 14(12), 2091-2106, 2005.
- [21] Li S.T., Shawe-Taylor J.: Comparison and fusion of multiresolution features for texture classification. PRL, 26(5), 633-638, 2005.
- [22] Selesnick I.W., Baraniuk R.G., Kingsbury N. C.: The dual-tree complex wavelet transform. IEEE Trans. SPM, 22(6), 123-151, 2005.
- [23] Arivazhagan S., Ganesan L., Subash Kumar T.G.: Texture classification using ridgelet transform. PRL, 27(16), 1875-1883, 2006.
- [24] Candes E.J., Demanet L., Donoho D.L.: Fast discrete curvelet transforms. MM&S, 5(3), 861-899, 2006.
- [25] Kim S.C., Kang T.J.: Texture classification and segmentation using wavelet packet frame and Gaussian mixture model. PR, 40(4), 1207-1221, 2007.
- [26] Dettori L., Semler L.: A comparison of wavelet, ridgelet, and curvelet-based texture classification algorithms in computed tomography. CB&M, 37(4), 486-498, 2007.
- [27] Sengur A.: Wavelet transform and adaptive neuro-fuzzy inference system for color texture classification. ESA, 34(3), 2120-2128, 2008.
- [28] Li S.T., Fu X.M., Yang B.: Nonsubsampled contourlet transform for texture classifications using support vector machines. Proc. ICNSC, pp. 1654-1657, 2008.
- [29] Turkoglu I., Avci E.: Comparison of wavelet-SVM and wavelet-adaptive network based fuzzy infer ence system for texture classification. DSP, 18(1),15-24, 2008.
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-article-BWA9-0032-0004