A review of recent texture segmentation and feature extraction techniques

Computer Vision and Image Understanding

Volumn 57, Issue 3, 1993, Pages 359-372

  Reed, Todd R ^a   du Buf, J M Hans ^b  

^a UNIVERSITY OF CALIFORNIA   (United States)

^b EPFL   (Switzerland)

Author keywords

[No Author keywords available]

Indexed keywords

EID: 44949269634     PISSN: 10773142     EISSN: 1090235X     Source Type: Journal    
DOI: 10.1006/cviu.1993.1024     Document Type: Review

References (96)

1. R. M. Haralick, Statistical and structural approaches to texture, Proc. IEEE 67, 1979, 786-804.
2. L. S. Davis, Image texture analysis techniques-A survey, in Digital Image Processing (J. C. Simon and R. M. Haralick, Eds.), pp. 189-201, Reidel, Dordrecht, 1981.
3. L. Van Gool, P. Dewaele, and A. Oosterlinck, Texture analysis anno 1983, Compnt. Vision Graphics Image Process. 29, 1985, 336-357.
4. R. M. Haralick, Image segmentation survey, in Fundamentals in Computer Vision (O. D. Faugeras, Ed.), pp. 209-224, Cambridge Univ. Press, Cambridge, 1983.
5. R. M. Haralick and L. M. Shapiro, Image segmentation techniques, Comput. Vision Graphics Image Process. 29, 1985, 100-132.
6. K. I. Laws, Textared Image Segmentation, Technical Report USCIPI Report 940, Dept, of Elec. Eng., Image Processing Institute, Univ. of Southern California, Los Angeles. January 1980.
7. R. W. Conners, M. M. Trivedi, and C. A. Harlow, Segmentation of a high-resolution urban scene using texture operators, Comput. Vision Graphics Image Process. 25, 1984, 273-310.
8. R. M. Haralick, K. Shanmugam, and J. Dinstein, Textural features for image classification, IEEE Trans. Systems Man Cybernet. 3(1), 1973, 610-621.
9. I. Dinstein, A. C. Fong, L. M. Ni, and K. Y. Wong, Fast discrimination between homogeneous and textured regions, in Proceedings, 7th International Conference on Pattern Recognition, Montreal, Canada, July 30-August 2, 1984, pp. 361-363.
10. M. Unser, Local linear transforms for texture measurements, Signal Process. 11, 1986, 61-79.
11. R. Wang, A. R. Hanson, and E. M. Riseman, Texture analysis based on local standard deviation of intensity, IEEE Computer Society Conference on Computer Vision and Pattern Recognition, Miami Beach, Florida, June 22-26, 1986, pp. 482-488.
12. G. H. Granlund, Description of texture using the genera) operator approach, in Proceedings, 5th International Conference on Pattern Recognition, Miami Beach, Florida, December 1-4, 1980, pp. 776-779.
13. D. Wermser and N. Lissel, Comparison of algorithms for unsupervised segmentation of images by the use of texture information, in Proceedings of the 2nd European Signal Processing Conference, Erlangen, West Germany, September 12-16, 1983, pp. 287-290.
14. L. W. Abele, Feature selection by space invariant comparison with applications to the segmentation of textured pictures, in Proceedings of the 5th International Conference on Pattern Recognition, Miami Beach, Florida, December 1-4, 1980, pp. 535-539.
15. P. C. Chen and T. Pavlidis, Segmentation by texture using a cooccurence matrix and a split-and-merge algorithm, Comput. Graphics Image Process. 10, 1979, 172-182.
16. H. Knutsson and G. H. Granlund, Texture analysis using two-dimensional quadrature filters, in IEEE Workshop CAPAIDM, Pasadena, CA, 1983, pp. 206-213.
17. J. Bigun, Frequency and orientation selective texture measures using linear symmetry and Laplacian pyramid, in Proceedings Visual Communications and Image Processing, Lausanne, Switzerland, October 2-4, 1990, pp. 1319-1331.
18. H. Tamura, S. Mori, and T. Yamawaki, Texture features corresponding to visual perception, IEEE Trans. Systems Man Cybernet. 8, 1978, 460-473.
19. P. A. Dondes and A. Rosenfeld, Pixel classification based on gray level and local "busyness," IEEE Trans. Pattern Anal. Mach. Intell. 4(1), 1982, 79-84.
20. P. de Souza, Edge detection using sliding statistical tests, Comput. Vision Graphics Image Process. 23, 1983, 1-14.
21. H. Y. Lee, Extraction of textured regions in aerial imagery, in Image Understanding, Proceedings, Workshop, Arlington, VA, June 23, 1983 (L. S. Baumann, Ed.), pp. 298-303, Science Appi., Mc Lean, VA, 1983.
22. G.E. Lowitz, Can a local histogram really map texture information?. Pattern Recognit. 16(2), 1983, 141-147.
23. D. B. C. Shu, Y. N. Sun, C. C. Li, and J. F. Mancuso, Run length based image segmentation schemes, in Proceedings, IEEE Computer Society Conference on Computer Vision and Pattern Recognition, Washington, DC, June 19-23, 1983, pp. 154-156.
24. M. Sato and M. Ogata, Texture analysis by the self-organization method, in Proceedings, 7th International Conference on Pattern Recognition, Montreal, Canada, July 30-August 2, 1984, pp. 1213-1215.
25. G. Y. Xu and K. S. Fu, Natural scene segmentation based on multiple threshold and texture measurement, in Proceedings, 7th International Conference on Pattern Recognition, Montreal, Canada, July 30-August 2, 1984, pp. 1111-1113.
26. M. E. Jernigan and F. D’Astous, Entropy-based texture analysis in the spatial frequency domain, IEEE Trans. Pattern Anal. Much. Intell. 6(2), 1984, 237-243.
27. F. D’Astous and M. E. Jernigan, Texture discrimination based on detailed measures of the power spectrum, in Proceedings, 7th International Conference on Pattern Recognition, Montreal, Canada, July 30-August 2, 1984, pp. 83-86.
28. H. Wechsler, Taxonomy and segmentation of textured images, in Proceedings, 5th International Conference on Pattern Recognition, Miami Beach, Florida, December 1-4, 1980, pp. 532-534.
29. D. Barba and J. Ronsin, New method in texture analysis in the context of image segmentation, in Proceedings, 2nd European Signal Processing Conference, Erlangen, West Germany, September 12-16, 1983, pp. 283-286.
30. B. Ashjari, Computer detection and identification of a visually indis-cernable texture mixture, in Proceedings, IEEE Computer Society Conference on Computer Vision and Pattern Recognition, San Francisco, CA, June 19-23, 1985, pp. 172-174.
31. B. P. Kjell and C. R. Dyer, Segmentation of textured images, in Proceedings, IEEE Computer Society Conference on Computer Vision and Pattern Recognition, Miami Beach, Florida, June 22-26, 1986, pp. 476-481.
32. L. S. Davis and A. Mitiche, Mites: A model-driven, iterative texture segmentation algorithm, Comput. Graphics Image Process. 19, 1982, 95-110.
33. R. Lumia, R. M. Haralick, O. Zuniga, L. Shapiro, T. C. Pong, and F. P. Wang, Texture analysis of aerial photographs, Pattern Recognit. 16(1), 1983, 39-46.
34. M. Pietikainen and A. Rosenfeld, Image segmentation by texture using pyramid node linking, IEEE Trans. Systems Man Cybernet. 11(12), 1981, 822-825.
35. H. M. Raafat and A. K. C. Wong, Texture information directed algorithm for biological image segmentation and classification, in Proceedings, International Conference on Cybernetics and Society, Cambridge, Massachusetts, October 8-10, 1980, pp. 1003-1008.
36. H. M. Raafat and A. K. C. Wong, Texture-based image segmentation, in Proceedings, IEEE Computer Society Conference on Computer Vision und Pattern Recognition, Miami Beach, Florida, June 22-26, 1986. pp. 469-475.
37. P. W. Verbeek and D. J. de Jong, Edge preserving texture analysis, in Proceedings, 7th International Conference on Pattern Recognition, Montreal, Canada, July 30-August 2, 1984, pp. 1030-1032.
38. M. F. Doherty, C. M. Bjorklund, and M. T. Noga, Split-merge-merge: An enhanced segmentation capability, in Proceedings, IEEE Computer Society Conference on Computer Vision and Pattern Recognition, Miami Beach, Florida, June 22-26, 1986, pp. 325-330.
39. T. R. Reed, H. Wechsler, and M. Werman, Texture segmentation using a diffusion region growing technique, Pattern Recognit. 23(9), 1990, 953-960.
40. S. Grinaker, Edge based segmentation and texture separation, in Proceedings, 5th International Conference on Pattern Recognition. Miami Beach, Florida. December 1-4, 1980, pp. 554-557.
41. D. Wermser, Unsupervised segmentation by use of a texture gradient, in Proceedings, 7th International Conference on Pattern Recognition, Montreal, Canada, July 30-August 2, 1984, pp. 1114-1116.
42. A. M. Nazif and M. D. Levine, Low level image segmentation: An expert system, IEEE Trans. Pattern Anal. Much. Intell. 6(5), 1984, 555-577.
43. R. Ohlander, Analysis of Natural Scieces, Ph.D. thesis, Carnegie-Mellon University, Pittsburgh. PA, April 1975.
44. S. Tanimoto and T. Pavlidis, A hierarchical data structure for picture processing, Comput. Graphics Image Process. 4, 1975, 104-119.
45. M. D. Levine and A. M. Nazif, Dynamic measurement of computer generated image segmentations, IEEE Trans. Pattern Anal. Much. Intell. 7(2) 1985. 155-164.
46. T. Pavlidis, Comments on "low level segmentation: an expert system," IEEE Trans. Pattern Anal. Much. Intell. 8(5), 1986, 675-676.
47. M. Spann and R. Wilson, A quad-tree approach to image segmentation which combines statistical and spatial information. Pattern Recognit. 18(3/4), 1985, 257-269.
48. R. L. Kashyap, Image models, in Handbook of Pattern Recognition and Image Processing (T. Y. Young and K. S. Fu, Ed.) Chap. 12. pp. 281-310, Academic Press, New York, 1986.
49. A. P. Pentland, Fractal-based description of natural scenes, IEEE Trans. Pattern Anal. Much. Intell. 6(6), 1984, 661-674.
50. G. G. Medioni and Y. Yasumoto, A note on using the fractal dimension for segmentation, in IEEE Computer Vision Workshop, Annapolis, MD, 1984, pp. 25-30.
51. S. Peleg, J. Naor, R. Hartley, and D. Avnir, Multiple resolution texture analysis and classification, IEEE Trans. Pattern Anal. Mach. Intel). 6, 1984, 518-523.
52. P. T. Nguyen and J. Quinqueton, Space filling curves and texture analysis, in Proceedings, 6th Int. Conf. on Pattern Recognition, Munich, Germany, 1982, pp. 282-285.
53. A. Khotanzad and A. Bouarfa, A parallel, non-parametric, noniterative clustering algorithm with application to image segmentation, in Proceedings, 22nd Asilomar Conference on Signals, Systems, and Computers, IEEE Computer Society, Pacific Grove, CA, October 31-November 2, 1988 (R. R. Chen, Ed.), pp. 305-309.
54. A. Khotanzad and J. Chen, Unsupervised segmentation of textured images by edge detection in multidimensional features, IEEE Trans. Pattern Anal. Mach. Intell. 11(4), 1989, 414-421.
55. N. K. Huang, Markov model for image segmentation, in Proceedings, 22nd Allerton Conference on Communication, Control, and Computing, Montecello, IL, October 3-5, 1984, pp. 775-781.
56. N. K. Huang and X. Gong, Textured image recognition using the hidden Markov model, in Proceedings of the International Conference on Acoustics, Speech and Signal Processing-88, New York, NY, April 11-14, 1988, pp. 1128-1131.
57. X. Gong and N. K. Huang, Texture segmentation using iterative estimate of energy states, in Proceedings, 9th International Conference on Pattern Recognition, Rome, Italy, November 14-17, 1988, pp. 51-55.
58. J. E. Bevington and R. M. Mersereau, A random field model based algorithm for textured image segmentation, in Proceedings, 3rd European Signal Processing Conference, The Hague, The Netherlands, September 2-5, 1986, pp. 909-912.
59. S. Geman and D. Geman, Stochastic relaxation, Gibbs distributions, and Bayesian restoration of images, IEEE Trans. Pattern Anal. Mach. Intell. 6(6), 1984, 721-741.
60. H. Derin and H. Elliot, Modeling and segmentation of noisy and textured images using Gibbs random fields, IEEE Trans. Pattern Anal. Mach. Intell. 9(1), 1987, 39-55.
61. R. L. Kashyap and K. Eom, Texture boundary detection based on long correlation model, in Proceedings, 23rd Allerton Conf. on Communication, Control, and Computing, Monticello, Illinois, October 2-4, 1985, pp. 314-323.
62. R. L. Kashyap and K. B. Eom, Texture boundary detection based on the long correlation model, IEEE Trans. Pattern Anal. Mach. Intell. 11, 1989, 58-67.
63. R. Chellappa and S. Chatterjee, Classification of textures using Gaussian Markov random fields, IEEE Trans. Acoust. Speech Signal Process. 33(4), 1985, 959-963.
64. T. Simchony and R. Chellappa, Stochastic and deterministic algorithms for MAP texture segmentation, in Proceedings, IEEE Int. Conf. on Acoustics, Speech, and Signal Processing, New York, NY, April 11-14, 1988, pp. 1120-1123.
65. J. Besag, On the statistical analysis of dirty pictures, J. R. Statist. Soc. B 48, 1986, 259-302.
66. B. S. Manjunath and R. Chellappa, Unsupervised texture segmentation using Markov random field models, IEEE Trans. Pattern Anal. Mach. Intell. 13(5), 1991, 478-482.
67. F. S. Cohen and D. B. Cooper, Simple parallel hierarchical and relaxation algorithms for segmenting noncausal Markovian random fields, IEEE Trans. Pattern Anal. Mach. Intell. 9(2), 1987, 195-219.
68. J. Silverman and D. Cooper, Bayesian clustering for unsupervised estimation of surfaces and texture models, IEEE Trans. Pattern Anal. Mach. Intell. 10(4), 1988, 482-495.
69. Z. Fan and F. S. Cohen, Textured image segmentation as a multiple hypothesis test, IEEE Trans. Circuits Systems 35(6), 1988, 691-702.
70. F. S. Cohen and Z. Fan, Maximum likelihood unsupervised textured image segmentation, Computer Vision Graphics Image Process. Graph. Models Image Process. 54(3), 1992, 239-251.
71. F. Cohen, Y. Liu, and Z. Fan, Detection and localization of edges in textured images modeled by gaussian markov random fields, in 13th GRETSI Symposium on Signal and Image Processing, Juans les Pins, France, September 16-20, 1991, pp. 1161-1164.
72. S. N. Jayaramamurthy, Texture discrimination using digital deconvolution filters, in Proceedings, 5th International Conference on Pattern Recognition, Miami Beach, Florida, December 1-4, 1980, pp. 1184-1186.
73. T. Matsuyama, K. Saburi, and M. Nagao, A structural analyzer for regularly arranged textures, Comput. Graphics Image Process. 18, 1982, 259-278.
74. J. Toriwaki, Y. Yashima, and S. Yokoi, Adjacency graphs on a digitized figure set and their applications to texture analysis, in Proceedings, 7th International Conference on Pattern Recognition, Montreal, Canada, July 30-August 2, 1984, pp. 1216-1218.
75. R. W. Connors and C. A. Harlow, A theoretical comparison of lexture algorithms, IEEE Trans. Pattern Anal. Mach. Intell. 2(3), 1980, 204-222.
76. J. S. Weszka, C. R. Dyer, and A. Rosenfeld, A comparison study of texture measures for terrain classification, IEEE Trans. Systems Man Cybernet. 6(4), 1976, 269-286.
77. F. H. C. Crick, D. C. Marr, and T. Poggio, An Information Processing Approach to Understanding the Visual Cortex, A. I. Memo 557, MIT, April 1980.
78. J. G. Daugman, Uncertainty relation for resolution in space, spatial frequency, and orientation optimized by two-dimensional visual cortical filters, J. Opt. Sac. Am. A 2(7), 1985, 1160-1169.
79. A. B. Watson, The cortex transform: Rapid computation of simulated neural images, Compitt. Vision Graphics Image Process. 39, 1987, 311-327.
80. A. P. Ginsburg, Specifying relevant spatial information for image evaluation and display design: An explanation of how we see certain objects, Proc. SID 21(3), 1980, 219-227.
81. J. Beck, A. Sutter, and R. Ivry, Spatial frequency channels and perceptual grouping in texture segregation, Comput. Vision Graphics Image Process. 37, 1987, 299-325.
82. T. R. Reed and H. Wechsler, Tracking of non-stationarities for texture fields, Signal Process. 14(1), 1988, 95-102.
83. T. R. Reed and H. Wechsler, Segmentation of textured images and Gestalt organization using spatial/spatial-frequency representations, IEEE Trans. Pattern Anal. Much. Intell. 12(1), 1990, 1-12.
84. T. R. Reed and H. Wechsler, Spatial/spatial-frequency representations for image segmentation and grouping, Image Vision Comput. 9(3), 1991, 175-193.
85. M. R. Turner, Texture discrimination by Gabor functions, Biol. Cybernet. 55, 1986, 71-82.
86. A. K. Jain and F. Farrokhnia, Unsupervised texture segmentation using Gabor filters, Pattern Recognit. 24(12), 1991, 1167-1186.
87. A. C. Bovik, M. Clark, and W. S. Geisler, Multichannel texture analysis using localized spatial filters, IEEE Trans. Pattern Anal. Much. Intell. 12, 1990, 55-73.
88. J. M. H. du Buf, Abstract processes in texture discrimination, Spatial Vision 6(3), 1992, 221-242.
89. J. Bigun and J. M. H. du Buf, Texture segmentation by real and complex moments of the Gabor power spectrum, in Progress in Image Analysis and Processing II (V. Cantoni et al., Eds.), pp. 191-198, World Scientific, Singapore, 1992.
90. J. Bigun and J. M. H. du Buf, N-folded symmetries by complex moments in Gabor space and their application to texture segmentation, IEEE Trans. Pattern Anal. Much. Intell., in press.
91. J. M. H. du Buf, Towards unsupervised texture segmentation using Gabor spectral decomposition, in Progress in Image Analysis and Processing (V. Cantoni, L. P. Cordelia, S. Levialdi, and G. Sanniti di Baja, Ed.), pp. 65-72, World Scientific, Singapore, 1990.
92. J. M. H. du Buf, Gabor phase in texture discrimination. Signal Process. 21, 1990, 221-240.
93. J. M. H. du Buf and P. Heitkamper, Texture features based on Gabor phase, Signal Process. 23, 1991, 227-244.
94. C. H. Chen, On the statistical image segmentation techniques, in Proceedings, IEEE Computer Society Conference on Pattern Recognition and Image Processing, Dallas, Texas, August 3-5, 1981, pp. 262-266.
95. M. Pietikainen, Image Texture Analysis and Segmentation, Ph.D. thesis. University of Oulu, Finland, 1982.
96. J. M. H. du Buf, M. Kardan, and M. Spann, Texture feature performance for image segmentation. Pattern Recognit. 23(3/4), 1990. 291-309.