This Article 
   
 Share 
   
 Bibliographic References 
   
 Add to: 
 
Digg
Furl
Spurl
Blink
Simpy
Google
Del.icio.us
Y!MyWeb
 
 Search 
   
Filtering for Texture Classification: A Comparative Study
April 1999 (vol. 21 no. 4)
pp. 291-310

Abstract—In this paper, we review most major filtering approaches to texture feature extraction and perform a comparative study. Filtering approaches included are Laws masks, ring/wedge filters, dyadic Gabor filter banks, wavelet transforms, wavelet packets and wavelet frames, quadrature mirror filters, discrete cosine transform, eigenfilters, optimized Gabor filters, linear predictors, and optimized finite impulse response filters. The features are computed as the local energy of the filter responses. The effect of the filtering is highlighted, keeping the local energy function and the classification algorithm identical for most approaches. For reference, comparisons with two classical nonfiltering approaches, co-occurrence (statistical) and autoregressive (model based) features, are given. We present a ranking of the tested approaches based on extensive experiments.

[1] T.R. Reed and J.M.H. du Buf,“A review of recent texture segmentation and feature extraction techniques,” Computer Vision, Graphics, and Image Process, vol. 57, pp. 359-372, May 1993.
[2] M. Tuceryan and A.K. Jain, “Texture Analysis,” Handbook Pattern Recognition and Computer Vision, C.H. Chen, L.F. Pau, and P.S.P. Wang, eds., Singapore: World Scientific, pp. 235-276, 1993.
[3] K.I. Laws, "Rapid Texture Identification," Proc. SPIE Conf. Image Processing for Missile Guidance, pp. 376-380, 1980.
[4] J.S. Weszka, C.R. Dyer, and A. Rosenfeld, "A Comparative Study of Texture Measures for Terrain Classification," IEEE Trans. Systems, Man, Cybernetics, vol. 6, pp. 269-285, Apr. 1976.
[5] R.W. Conners and C.A. Harlow, "A Theoretical Comparison of Texture Algorithms," IEEE Trans. Pattern Analysis and Machine Intelligence, vol. 2, pp. 204-221, May 1980.
[6] J.M.H. du Buf,M. Kardan,, and M. Spann,“Texture feature perfor-mance for image segmentation,” Pattern Recognition, vol. 23, pp. 291-309, 1990.
[7] J. Strand and T. Taxt, "Local Frequency Features for Texture Classification," Pattern Recognition, vol. 27, no. 10, pp. 1,397-1,406, 1994.
[8] M. Pietikäinen, A. Rosenfeld, and L.S. Davis, "Experiments with Texture Classification Using Averages of Local Pattern Matches," IEEE Trans. Systems, Man, Cybernetics, vol. 13, no. 3, pp. 421-426, 1983.
[9] D. Clausi and M. Jernigan, "Towards a Novel Approach for Segmentation of SAR Sea Ice Imagery," Proc. 26th Symp. Remote Sensing of Environment and 18th Ann. Symp. Canadian Remote Sensing Society, Mar. 1995.
[10] T. Ojala, M. Pietikäinen, and D. Harwood, "A Comparative Study of Texture Measures with Classification Based on Feature Distributions," Pattern Recognition, vol. 29, no. 1, pp. 51-59, 1996.
[11] M. Unser, Texture Classification and Segmentation Using Wavelet Frames IEEE Trans. Image Processing, vol. 4, no. 11, pp. 1549-1560, Nov. 1995.
[12] J.M. Coggins and A.K. Jain, "A Spatial Filtering Approach to Texture Analysis," Pattern Recognition Letters, vol. 3, no. 3, pp. 195-203, 1985.
[13] F. Ade, "Characterization of Texture by 'Eigenfilter,'" Signal Processing, vol. 5, no. 5, pp. 451-457, 1983.
[14] A.C. Bovik,M. Clark,, and W.S. Geisler,“Multichannel texture analysis using localized spatial filters,” IEEE Trans. Pattern Analysis and Machine Intelligence, vol. 12, pp. 55-73, 1990.
[15] T.P. Weldon and W.E. Higgins, "Design of Multiple Gabor Filters for Texture Segmentation," Proc. Int'l Conf. Acoustic Speech, Signal Proc.,Atlanta, Ga., pp. 2,243-2,246, May 1996.
[16] T.P. Weldon and W.E. Higgins, "Integrated Approach to Texture Segmentation Using Multiple Gabor Filters," Proc. Int'l Conf. Image Processing,Lausanne, Switzerland, pp. 955-958, Sept. 1996.
[17] T. Randen and J.H. Husøy, "Multichannel Filtering for Image Texture Segmentation," Optical Eng., vol. 33, pp. 2,617-2,625, Aug. 1994.
[18] T. Randen and J.H. Husøy, "Texture Segmentation Using Filters with Optimized Energy Separation," IEEE Trans. Image Processing, vol. 8, no. 4, Apr. 1999.
[19] F. Farrokhnia, "Multi-Channel Filtering Techniques for Texture Segmentation and Surface Quality Inspection," PhD thesis, Michigan State Univ., 1990.
[20] A.K. Jain and F. Farrokhnia, “Unsupervised Texture Segmentation Using Gabor Filters,” Pattern Recognition, vol. 24, no. 12, pp. 1167-1186, 1991.
[21] A. Laine and J. Fan, “Texture Classification by Wavelet Packet Signature,” IEEE Trans. Pattern Analysis and Machine Intelligence, vol. 15, no. 11, pp. 1,186-1,191, Nov. 1993.
[22] P.P. Ohanian and R.C. Dubes, "Performance Evaluation for Four Classes of Textural Features," Pattern Recognition, vol. 25, no. 8, pp. 819-833, 1992.
[23] M. Unser, "Local Linear Transforms for Texture Measurements," Signal Processing, vol. 11, no. 1, pp. 61-79, 1986.
[24] T. Chang and C.-C.J. Kuo, "Texture Analysis and Classification With Tree-Structured Wavelet Transform," IEEE Trans. Image Processing, vol. 2, no. 4, pp. 429-441, Oct. 1993.
[25] A. Teuner, O. Pichler, and B.J. Hosticka, "Unsupervised Texture Segmentation of Images Using Tuned Matched Gabor Filters," IEEE Trans. Image Processing, vol. 4, pp. 863-870, June 1995.
[26] N. Saito and R.R. Coifman, "Local Discriminant Bases and Their Applications," J. Mathematical Imaging and Vision, vol. 5, no. 4, pp. 337-358, 1995.
[27] M. Unser and M. Eden, "Nonlinear Operators for Improving Texture Segmentation Based on Features Extracted by Spatial Filtering," IEEE Trans. Systems, Man, Cybernetics, vol. 20, pp. 804-815, 1990.
[28] R. Duda, P. Hart, and D. Stork, Pattern Classification. New York: John Wiley&Sons, 2001.
[29] K. Fukunaga, Introduction to Statistical Pattern Recognition, second edition. Academic Press, 1990.
[30] R.J. Schalkoff, Pattern Recognition: Statistical, Structural and Neural Approaches.New York: John Wiley and Sons, 1992.
[31] A. Mahalanobis and H. Singh, "Application of Correlation Filters for Texture Recognition," Applied Optics, vol. 33, no. 11, pp. 2,173-2,179, 1994.
[32] T. Randen and J.H. Husøy, "Texture Segmentation with Optimal Linear Prediction Error Filters," Piksel'n, vol. 11, pp. 25-28, Sept. 1994. Also available athttp://www.ux.his.no~tranden/.
[33] T. Randen, "Filter and Filter Bank Design for Image Texture Recognition," PhD thesis, Norwegian Univ. of Science and Tech nology, Trondheim, Norway, Oct. 1997. Also available athttp://www.ux.his.no~tranden/.
[34] J. Mao and A.K. Jain, “Texture Classification and Segmentation Using Multiresolution Simultaneous Autoregressive Models,” Pattern Recognition, vol. 25, no. 2, 1992.
[35] T. Kohonen, "The Self-Organizing Map," Proc. IEEE, vol. 78, pp. 1,464-1,480, Sept. 1990.
[36] R. Haralick, K. Shanmugam, and I. Dinstein, "Textural Features for Image Classification," IEEE Trans. Systems, Man, Cybernetics, vol. 3, pp. 610-621, Nov. 1973.
[37] A.N. Akansu and R.A. Haddad, Multiresolution Signal Decomposition.San Diego, Calif.: Academic Press, 1992.
[38] S.G. Mallat,“A theory for multiresolution signal decomposition: The wavelet representation,” IEEE Trans. Pattern Analysis and Machine Intelligence, vol. 11, no. 7, pp. 674-693, 1989.
[39] I. Daubechies, Wavelets.Philadelphia, Pa.: S.I.A.M, 1992.
[40] T.A. Ramstad, S.O. Aase, and J.H. Husøy, Subband Compression of Images—Principles and Examples.North Holland: ELSEVIER Science Publishers BV, 1995.
[41] I. Ng, T. Tan, and J. Kittler, "On Local Linear Transform and Gabor Filter Representation of Texture," Proc. Int'l Conf. Pattern Recognition, pp. 627-631. Int'l Assoc. for Pattern Recognition, 1992.
[42] J.D. Johnston, "A Filter Family Designed for Use in Quadrature Mirror Filter Banks," Proc. Int'l Conf. Acoustic Speech, Signal Processing,Denver, Colo., pp. 291-294, 1980.
[43] J.H. Husøy, "Low Complexity Subband Coding of Still Images and Video," Optical Eng., vol. 30, pp. 904-911, July 1991.
[44] D.F. Dunn and W.E. Higgins, "Optimal Gabor Filters for Texture Segmentation," IEEE Trans. Image Processing, vol. 4, pp. 947-964, July 1995.
[45] A.K. Jain and K. Karu, “Learning Texture Discrimination Masks,” IEEE Trans. Pattern Analysis Machine Intelligence, vol. 18, no. 2, pp. 195-205, Feb. 1996.
[46] D.W. Pagliero,“Distance transforms,” Computer Vision, Graphics, and Image Processing: Graphical models and Image Processing, vol. 54, pp. 56-74, 1992.
[47] P. Brodatz, Textures: A Photographic Album for Artists and Designers.New York: Dover, 1966.
[48] MIT Vision and Modelling Group, http://www.media.mit.eduvismod/, 1998.
[49] MeasTex Image Texture Database, http://www.cssip.elec.uq.edu.au/~guy/meastex meastex.html, 1998.
[50] D.F. Dunn, W.E. Higgins, and J. Wakeley, "Texture Segmentation Using 2-D Gabor Elementary Functions," IEEE Trans. Pattern Analysis and Machine Intelligence, vol. 22, pp. 130-149, Feb. 1994.

Index Terms:
Texture classification, image processing, filtering, survey.
Citation:
Trygve Randen, John Håkon Husøy, "Filtering for Texture Classification: A Comparative Study," IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 21, no. 4, pp. 291-310, April 1999, doi:10.1109/34.761261
Usage of this product signifies your acceptance of the Terms of Use.