references - Shodhganga
REFERENCES 1.
Anagnostopoulos, C., Vergados, D., Kayafas, E., Loumos, V., and Stassinopoulos, G., 2001. A Computer Vision Approach for Textile Quality Control. Journal of Visualization and Computer Animation 12, 31–44.
2.
Bhajantri, N.U., Nagabhushan, P., 2006. Camouflage Defect Identification: A Novel Approach. In: Proceedings of ICIT 2006, pp. 145–148.
3.
Brodatz, P., 1966. Textures: A Photographic Album for Designers and Artists, Dover, New York.
4.
Brown, C.D., Davis, H.T., 2006. Receiver operating characteristics curves and related decision measures: Chemometrics and Intelligent Laboratory Systems 80, 24–38.
5.
Campello, R., 2007. A Fuzzy Extension of the Rand Index and Other Related Indexes for Clustering and Classification Assessment. Pattern Recognition Letters 28 (7), 833–841.
6.
Chin, R.T., Harlow, C.A., 1982. Automated visual inspection: A survey. IEEE Transactions on Pattern Analysis and Machine Intelligence 4 (6), 557–573.
7.
Cho, C., Chung, B., and Park, M., 2005. Development of Real-Time Vision-Based Fabric Inspection System. IEEE Transactions on Industry Electronics 52 (4), 1073– 1079.
8.
Conners, R.W., Harlow, C.A., 1980. Toward a structural analyzer based on statistical methods. Computer, Graphics and Image Processing 12 (3), 224–256.
9.
Coxeter, H.S.M., Moser, W.O.J., 1980. Generators and Relations for Discrete Groups, Fourth Ed., Springer-Verlag, New York.
10.
Davies, D.L., Bouldin, D.W., 1979. A Cluster Separation Measure. IEEE Transactions on Pattern Analysis and Machine Intelligence 1 (2), 224–227.
11.
Daugman, J.D., 1980. Two-dimensional spectral analysis of cortical receptive field profiles. Vision Research 20, 847–856.
12.
Daugman, J.D., 1987. Image analysis and compact coding by oriented 2-D Gabor primitives. SPIE Proceedings 758, 19–30.
13.
Dunn, J.C., 1974. Well Separated Clusters and Optimal Fuzzy Partitions. Cybernetics and Systems 4 (1), 95–104.
14.
Eli, P., 1990. Contrast in complex images. Journal of the Optical Society of America A 7 (10), 2032–2040.
159
15.
Endres, D.M., Schindelin, J.E., 2003. A New Metric for Probability Distributions. IEEE Transactions on Information Theory 49 (7), 1858–1860.
16.
Fawcett, T., 2006. An introduction to ROC analysis. Pattern Recognition Letters 27 (8), 861–874.
17.
Fernendes, J.C.A., Campos Neves, J.A.B., Couto, C.A.C., 1999. Defect Detection and Localization in Textiles using Co-occurrence matrices and Morphological Operators. In: Proceedings of the 6th International Conference on Mechatronics and Machine Vision in Practice (M2VIP99), Ankara, Turkey, pp. 81–86.
18.
Fred, A.L.N., Jain, A.K., 2005. Combining Multiple Clusterings Using Evidence Accumulation. IEEE Transactions on Pattern Analysis and Machine Intelligence 27 (6), 835–850.
19.
Gonzalez, R.C., Woods, R.E., 2008. Digital Image Processing, Third Edition, Pearson Prentice Hall, New Delhi.
20.
Grigorescu, S.E., Petkov, N., 2003. A dynamical system approach to texel identification in regular textures. In: Proceedings of the 3rd International Symposium on Image and Signal Processing and Analysis 1, pp. 66–71.
21.
Grigorescu, S.E., Petkov, N., 2003. Texture Analysis using Renyi‟s Generalized Entropies. In: Proceedings of IEEE International Conference on Image Processing 1, pp. 241–244.
22.
Gururajan, A., Sari-Sarraf, H., Hequet, E.F., 2008. Statistical Approach to Unsupervised Defect Detection and Multi-Scale Localization in Two-Texture Images. Optical Engineering 47 (2), 027202-1–027202-10.
23.
Haralick, R. M., Shanmugam, K., Dinstein, I., 1973. Textural features for image classification. IEEE Transactions on Systems, Man, and Cybernetics SMC-3, 610–621.
24.
Jain, A.K., Farrokhnia, F., 1990. Unsupervised Texture Segmentation Using Gabor Filters. In: Proceedings of the IEEE Conference on Systems, Man, and Cybernetics, pp. 14–19.
25.
Jain, A.K., Murty, M.N., Flynn, P.J., 1999. Data Clustering: A Review. ACM Computing Survey 31 (3), 264–323.
26.
Johnson, R.A., Wichern, D.W., 2009. Applied Multivariate Statistical Analysis, Fifth Edition, PHI Learning Private Limited, New Delhi.
160
27.
Jones, O., 1853. The Grammar of Ornament. Lewis, M. (Ed.), Dorling Kindersley Publisher, London, 2001. Available from http://ebookee.org/TheGrammar-of-Ornament-by-Owen-Jones_62700.html.
28.
Jukka, I., Juhani, R., and Ari, V., 1996. Unsupervised Segmentation of Surface Defects. In: IEEE Proceedings of ICPR '96, pp. 356–360.
29.
Julesz, B., 1962. Visual pattern discrimination. IRE Transactions on Information Theory IT-8 (2), 84–92.
30.
Khalaj, B.H., Kailath, T., 1994. Patterned wafer inspection by high resolution spectral estimation techniques, Machine Vision and Applications 7, 178–185.
31.
Kumar, A., 2001. Automated defect detection in textured materials. Ph.D Thesis. The University of Hong Kong.
32.
Laws, K.I., 1980. Texture Image Segmentation. Ph.D. Thesis. University of Southern California.
33.
Lee, T.S., 1996. Image representation using 2D Gabor wavelets. IEEE Transactions on Pattern Analysis and Machine Intelligence 18, 959–971.
34.
Leung, T., Malik, J., 2001. Representing and Recognizing the Visual Appearance of Materials using Three-dimensional Textons. International Journal of Computer Vision 43 (1), 29–44.
35.
Lin, H.C., Wang, L.L., Yang, S.N., 1997. Extracting periodicity of a regular texture based on autocorrelation functions. Pattern Recognition Letters 18 (5), 433–443.
36.
Lin, W.C., Hays, J., Wu, C., Kwatra, V., Liu, Y., 2006. Quantitative Evaluation of Near Regular Texture Synthesis Algorithm. In: Proceedings of IEEE Computer Society Conference on Computer Vision and Pattern Recognition 1, pp. 427–434.
37.
Liu, Y., Collins, R.T., Tsin, Y., 2004. A Computational Model for Periodic Pattern Perception Based on Frieze and Wallpaper Groups. IEEE Transactions on Pattern Analysis and Machine Intelligence 26 (3), 354–371.
38.
Liu, Y., Lin, W.-C., Hays, J., 2004. Near-Regular Texture Analysis and Manipulation. In: Proceedings of ACM SIGGRAPH Conference, pp. 368–376.
39.
Liu, Y., Tsin, Y., Lin, W.-C., 2005. The Promise and Perils of Near-regular Texture. International Journal of Computer Vision 61 (1-2), 145–159.
40.
Manjunath, B., Ma, W., 1996. Texture features for browsing and retrieval of image data. IEEE Trans on Pattern Analysis and Machine Intelligence 18, 837–842. 161
41.
Manjunath, B., Wu, P., Newsam, S., Shin, H., 2000. A texture descriptor for browsing and similarity retrieval. Journal of Signal Processing and Image Communication 16, 33-43.
42.
Matsuyama, T., Miura, S.-I., Nagao, M., 1983. Structural analysis of natural textures by Fourier transformation. Computer Vision, Graphics and Image Processing 24 (3), 347–362.
43.
Miquel, R., Maria, S.M., and Jaume, E., 2009. Unsupervised novelty detection using Gabor filters for defect segmentation in textures, Journal of the Optical Society of America A 26 (9), 1967–1976.
44.
Ngan, H.Y.T., Pang, G.H.K., Yung, S.P., Ng, M.K., 2005. Wavelet based methods on patterned fabric defect detection. Pattern Recognition 38 (4), 559–576.
45.
Ngan, H.Y.T., Pang, G.K.H., 2006. Novel method for patterned fabric inspection using Bollinger bands. Optical Engineering 45 (8), 1–15.
46.
Ngan, H.Y.T., Pang, G.K.H., Yung, N.H.C., 2008. Motif-based defect detection for patterned fabric. Pattern Recognition 41 (6), 1878–1894.
47.
Ngan, H.Y.T., Pang, G.H.K., 2009. Regularity Analysis for Patterned Texture Inspection. IEEE Transactions on Automation, Science and Engineering 6 (1), 131–144.
48.
Ngan, H.Y.T., Pang, G.H.K., Yung, N.H.C., 2010. Performance Evaluation for Motif-Based Patterned Texture Defect Detection IEEE Transactions on Automation, Science and Engineering 7 (1), 58–72.
49.
Ngan, H.Y.T., Pang, G.K.H., Yung, N.H.C., 2010. Ellipsoidal decision regions for motif-based patterned fabric defect detection, Pattern Recognition 43, 2132–2144.
50.
Nguyen, N., Caruana, R., 2007. Consensus Clusterings. In: Proceedings of IEEE International Conference on Data Mining, IEEE Computer Society, Washington, DC, pp. 607–612.
51.
Oh, G., Lee, S., Shin, S.Y., 1999. Fast determination of textural periodicity using distance matching function. Pattern Recognition Letters 20 (2), 191–197.
52.
Oh, G., Lee, S., 2002. Motif analysis of noisy regular textures. Pattern Recognition Letters 23 (10), 1179–1190.
53.
Parkkinen, J., Selkainaho, K., Oja, E., 1990. Detecting texture periodicity from the co-occurrence matrix. Pattern Recognition Letters 11 (1), 43–50.
162
54.
Pele, O., Werman, M., 2010. The Quadratic-Chi Histogram Distance Family, in: Daniilidis, K., Maragos, P., and Paragios, N. (Eds.): ECCV 2010, Part II, Lecture Notes in Computer Science 6312, pp. 749–762, Springer–Verlag, Berlin, Heidelberg.
55.
Penn State University, Near-Regular Texture database, 2010. Available from http://vivid.cse.psu.edu/texturedb/gallery.
56.
Qingxiang, W., Di, L., Wujie, Z., Dong, C., and Hao, C., 2010. Unsupervised Defect Detection of Flexible Printed Circuit Board Gold Surfaces Based on Wavelet Packet Frame. In: Proceedings of the 2nd International Conference on Industrial and Information Systems, pp. 324–327.
57.
Rand, W.M., 1971. Objective Criteria for the Evaluation of Clustering Methods. Journal of the American Statistical Association 66, 846–850.
58.
Rohrmus, D., 2000. Invariant Web Defect Detection and Classification System. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (2), pp. 794–795.
59.
Sandy, C., Norton, W.L., and Harwood, R., 1995. The Automated Inspection of Lace Using Machine Vision. Mechatronics Journal 5 (2/3), 215–231.
60.
Schattschneider, D., 1978. The Plane Symmetry Groups: Their Recognition and Notation. The American Mathematical Monthly 85, 439–450.
61.
Selkainaho, K., Parkkinen, J., Oja, E., 1988. Comparison of ψ2 and κ-statistics in finding signal and picture periodicity. In: Proceedings of the 9th ICPR, Rome, Italy, pp. 1221–1224.
62.
Soliman, S.S., Srinath, M.S., 1990. Continuous and Discrete Signals and Systems, Prentice-Hall, Englewood Cliffs, NJ, pp. 352–354.
63.
Starovoitov, V.V., Jeong, S.-Y., Park, R.-H., 1995. Investigation of texture periodicity extraction. In: SPIE Proceedings of Visual Communication and Image Processing, Taipei, Taiwan, R.O.C., pp. 870–881.
64.
Tajeripour, F., Kabir, E., Sheikhi, A., 2007. Fabric Defect Detection Using Modified Local Binary Patterns. In: Proceedings of the International Conference on Computational Intelligence and Multimedia Applications, pp. 261–267.
65.
Tamura, H., Mori, S., Yamawaki, T., 1978. Textural Features Corresponding to Visual Perception. IEEE Transactions on Systems, Man, and Cybernetics 8, 460–473.
66.
Theodoridis, S., Koutroumbas, K., 2009. Pattern Recognition, Fourth Edition, Academic Press, CA.
163
67.
Tuceryan, M., and Jain, A.K., 1998. Texture Analysis, in: Chen, C.H., Pau, L.F., and Wang, P.S.P. (Eds.): The Handbook of Pattern Recognition and Computer Vision (2nd Edition), World Scientific Publishing Company, pp. 207–248.
68.
Turner, M., 1986. Texture discrimination by Gabor functions. Biological Cybernetics 55, 71–82.
69.
Wang, Z., Bowik, C., 2002. A Universal Image Quality Index, IEEE Signal Processing Letters 9, 81–84.
70.
Weyl, H., 1952. Symmetry, Princeton University Press, New Jersey.
71.
Xie, P., Guan, S.U., 2000. A golden-template self-generating method for patterned wafer inspection. Machine Vision and Applications 12, 149–156.
72.
Yu, Z., Wong, H.S., Wang, H., 2007. Graph-Based Consensus Clustering for Class Discovery from Gene Expression Data. Bioinformatics 23 (21), 2888– 2896.
164
Anagnostopoulos, C., Vergados, D., Kayafas, E., Loumos, V., and Stassinopoulos, G., 2001. A Computer Vision Approach for Textile Quality Control. Journal of Visualization and Computer Animation 12, 31–44.
2.
Bhajantri, N.U., Nagabhushan, P., 2006. Camouflage Defect Identification: A Novel Approach. In: Proceedings of ICIT 2006, pp. 145–148.
3.
Brodatz, P., 1966. Textures: A Photographic Album for Designers and Artists, Dover, New York.
4.
Brown, C.D., Davis, H.T., 2006. Receiver operating characteristics curves and related decision measures: Chemometrics and Intelligent Laboratory Systems 80, 24–38.
5.
Campello, R., 2007. A Fuzzy Extension of the Rand Index and Other Related Indexes for Clustering and Classification Assessment. Pattern Recognition Letters 28 (7), 833–841.
6.
Chin, R.T., Harlow, C.A., 1982. Automated visual inspection: A survey. IEEE Transactions on Pattern Analysis and Machine Intelligence 4 (6), 557–573.
7.
Cho, C., Chung, B., and Park, M., 2005. Development of Real-Time Vision-Based Fabric Inspection System. IEEE Transactions on Industry Electronics 52 (4), 1073– 1079.
8.
Conners, R.W., Harlow, C.A., 1980. Toward a structural analyzer based on statistical methods. Computer, Graphics and Image Processing 12 (3), 224–256.
9.
Coxeter, H.S.M., Moser, W.O.J., 1980. Generators and Relations for Discrete Groups, Fourth Ed., Springer-Verlag, New York.
10.
Davies, D.L., Bouldin, D.W., 1979. A Cluster Separation Measure. IEEE Transactions on Pattern Analysis and Machine Intelligence 1 (2), 224–227.
11.
Daugman, J.D., 1980. Two-dimensional spectral analysis of cortical receptive field profiles. Vision Research 20, 847–856.
12.
Daugman, J.D., 1987. Image analysis and compact coding by oriented 2-D Gabor primitives. SPIE Proceedings 758, 19–30.
13.
Dunn, J.C., 1974. Well Separated Clusters and Optimal Fuzzy Partitions. Cybernetics and Systems 4 (1), 95–104.
14.
Eli, P., 1990. Contrast in complex images. Journal of the Optical Society of America A 7 (10), 2032–2040.
159
15.
Endres, D.M., Schindelin, J.E., 2003. A New Metric for Probability Distributions. IEEE Transactions on Information Theory 49 (7), 1858–1860.
16.
Fawcett, T., 2006. An introduction to ROC analysis. Pattern Recognition Letters 27 (8), 861–874.
17.
Fernendes, J.C.A., Campos Neves, J.A.B., Couto, C.A.C., 1999. Defect Detection and Localization in Textiles using Co-occurrence matrices and Morphological Operators. In: Proceedings of the 6th International Conference on Mechatronics and Machine Vision in Practice (M2VIP99), Ankara, Turkey, pp. 81–86.
18.
Fred, A.L.N., Jain, A.K., 2005. Combining Multiple Clusterings Using Evidence Accumulation. IEEE Transactions on Pattern Analysis and Machine Intelligence 27 (6), 835–850.
19.
Gonzalez, R.C., Woods, R.E., 2008. Digital Image Processing, Third Edition, Pearson Prentice Hall, New Delhi.
20.
Grigorescu, S.E., Petkov, N., 2003. A dynamical system approach to texel identification in regular textures. In: Proceedings of the 3rd International Symposium on Image and Signal Processing and Analysis 1, pp. 66–71.
21.
Grigorescu, S.E., Petkov, N., 2003. Texture Analysis using Renyi‟s Generalized Entropies. In: Proceedings of IEEE International Conference on Image Processing 1, pp. 241–244.
22.
Gururajan, A., Sari-Sarraf, H., Hequet, E.F., 2008. Statistical Approach to Unsupervised Defect Detection and Multi-Scale Localization in Two-Texture Images. Optical Engineering 47 (2), 027202-1–027202-10.
23.
Haralick, R. M., Shanmugam, K., Dinstein, I., 1973. Textural features for image classification. IEEE Transactions on Systems, Man, and Cybernetics SMC-3, 610–621.
24.
Jain, A.K., Farrokhnia, F., 1990. Unsupervised Texture Segmentation Using Gabor Filters. In: Proceedings of the IEEE Conference on Systems, Man, and Cybernetics, pp. 14–19.
25.
Jain, A.K., Murty, M.N., Flynn, P.J., 1999. Data Clustering: A Review. ACM Computing Survey 31 (3), 264–323.
26.
Johnson, R.A., Wichern, D.W., 2009. Applied Multivariate Statistical Analysis, Fifth Edition, PHI Learning Private Limited, New Delhi.
160
27.
Jones, O., 1853. The Grammar of Ornament. Lewis, M. (Ed.), Dorling Kindersley Publisher, London, 2001. Available from http://ebookee.org/TheGrammar-of-Ornament-by-Owen-Jones_62700.html.
28.
Jukka, I., Juhani, R., and Ari, V., 1996. Unsupervised Segmentation of Surface Defects. In: IEEE Proceedings of ICPR '96, pp. 356–360.
29.
Julesz, B., 1962. Visual pattern discrimination. IRE Transactions on Information Theory IT-8 (2), 84–92.
30.
Khalaj, B.H., Kailath, T., 1994. Patterned wafer inspection by high resolution spectral estimation techniques, Machine Vision and Applications 7, 178–185.
31.
Kumar, A., 2001. Automated defect detection in textured materials. Ph.D Thesis. The University of Hong Kong.
32.
Laws, K.I., 1980. Texture Image Segmentation. Ph.D. Thesis. University of Southern California.
33.
Lee, T.S., 1996. Image representation using 2D Gabor wavelets. IEEE Transactions on Pattern Analysis and Machine Intelligence 18, 959–971.
34.
Leung, T., Malik, J., 2001. Representing and Recognizing the Visual Appearance of Materials using Three-dimensional Textons. International Journal of Computer Vision 43 (1), 29–44.
35.
Lin, H.C., Wang, L.L., Yang, S.N., 1997. Extracting periodicity of a regular texture based on autocorrelation functions. Pattern Recognition Letters 18 (5), 433–443.
36.
Lin, W.C., Hays, J., Wu, C., Kwatra, V., Liu, Y., 2006. Quantitative Evaluation of Near Regular Texture Synthesis Algorithm. In: Proceedings of IEEE Computer Society Conference on Computer Vision and Pattern Recognition 1, pp. 427–434.
37.
Liu, Y., Collins, R.T., Tsin, Y., 2004. A Computational Model for Periodic Pattern Perception Based on Frieze and Wallpaper Groups. IEEE Transactions on Pattern Analysis and Machine Intelligence 26 (3), 354–371.
38.
Liu, Y., Lin, W.-C., Hays, J., 2004. Near-Regular Texture Analysis and Manipulation. In: Proceedings of ACM SIGGRAPH Conference, pp. 368–376.
39.
Liu, Y., Tsin, Y., Lin, W.-C., 2005. The Promise and Perils of Near-regular Texture. International Journal of Computer Vision 61 (1-2), 145–159.
40.
Manjunath, B., Ma, W., 1996. Texture features for browsing and retrieval of image data. IEEE Trans on Pattern Analysis and Machine Intelligence 18, 837–842. 161
41.
Manjunath, B., Wu, P., Newsam, S., Shin, H., 2000. A texture descriptor for browsing and similarity retrieval. Journal of Signal Processing and Image Communication 16, 33-43.
42.
Matsuyama, T., Miura, S.-I., Nagao, M., 1983. Structural analysis of natural textures by Fourier transformation. Computer Vision, Graphics and Image Processing 24 (3), 347–362.
43.
Miquel, R., Maria, S.M., and Jaume, E., 2009. Unsupervised novelty detection using Gabor filters for defect segmentation in textures, Journal of the Optical Society of America A 26 (9), 1967–1976.
44.
Ngan, H.Y.T., Pang, G.H.K., Yung, S.P., Ng, M.K., 2005. Wavelet based methods on patterned fabric defect detection. Pattern Recognition 38 (4), 559–576.
45.
Ngan, H.Y.T., Pang, G.K.H., 2006. Novel method for patterned fabric inspection using Bollinger bands. Optical Engineering 45 (8), 1–15.
46.
Ngan, H.Y.T., Pang, G.K.H., Yung, N.H.C., 2008. Motif-based defect detection for patterned fabric. Pattern Recognition 41 (6), 1878–1894.
47.
Ngan, H.Y.T., Pang, G.H.K., 2009. Regularity Analysis for Patterned Texture Inspection. IEEE Transactions on Automation, Science and Engineering 6 (1), 131–144.
48.
Ngan, H.Y.T., Pang, G.H.K., Yung, N.H.C., 2010. Performance Evaluation for Motif-Based Patterned Texture Defect Detection IEEE Transactions on Automation, Science and Engineering 7 (1), 58–72.
49.
Ngan, H.Y.T., Pang, G.K.H., Yung, N.H.C., 2010. Ellipsoidal decision regions for motif-based patterned fabric defect detection, Pattern Recognition 43, 2132–2144.
50.
Nguyen, N., Caruana, R., 2007. Consensus Clusterings. In: Proceedings of IEEE International Conference on Data Mining, IEEE Computer Society, Washington, DC, pp. 607–612.
51.
Oh, G., Lee, S., Shin, S.Y., 1999. Fast determination of textural periodicity using distance matching function. Pattern Recognition Letters 20 (2), 191–197.
52.
Oh, G., Lee, S., 2002. Motif analysis of noisy regular textures. Pattern Recognition Letters 23 (10), 1179–1190.
53.
Parkkinen, J., Selkainaho, K., Oja, E., 1990. Detecting texture periodicity from the co-occurrence matrix. Pattern Recognition Letters 11 (1), 43–50.
162
54.
Pele, O., Werman, M., 2010. The Quadratic-Chi Histogram Distance Family, in: Daniilidis, K., Maragos, P., and Paragios, N. (Eds.): ECCV 2010, Part II, Lecture Notes in Computer Science 6312, pp. 749–762, Springer–Verlag, Berlin, Heidelberg.
55.
Penn State University, Near-Regular Texture database, 2010. Available from http://vivid.cse.psu.edu/texturedb/gallery.
56.
Qingxiang, W., Di, L., Wujie, Z., Dong, C., and Hao, C., 2010. Unsupervised Defect Detection of Flexible Printed Circuit Board Gold Surfaces Based on Wavelet Packet Frame. In: Proceedings of the 2nd International Conference on Industrial and Information Systems, pp. 324–327.
57.
Rand, W.M., 1971. Objective Criteria for the Evaluation of Clustering Methods. Journal of the American Statistical Association 66, 846–850.
58.
Rohrmus, D., 2000. Invariant Web Defect Detection and Classification System. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (2), pp. 794–795.
59.
Sandy, C., Norton, W.L., and Harwood, R., 1995. The Automated Inspection of Lace Using Machine Vision. Mechatronics Journal 5 (2/3), 215–231.
60.
Schattschneider, D., 1978. The Plane Symmetry Groups: Their Recognition and Notation. The American Mathematical Monthly 85, 439–450.
61.
Selkainaho, K., Parkkinen, J., Oja, E., 1988. Comparison of ψ2 and κ-statistics in finding signal and picture periodicity. In: Proceedings of the 9th ICPR, Rome, Italy, pp. 1221–1224.
62.
Soliman, S.S., Srinath, M.S., 1990. Continuous and Discrete Signals and Systems, Prentice-Hall, Englewood Cliffs, NJ, pp. 352–354.
63.
Starovoitov, V.V., Jeong, S.-Y., Park, R.-H., 1995. Investigation of texture periodicity extraction. In: SPIE Proceedings of Visual Communication and Image Processing, Taipei, Taiwan, R.O.C., pp. 870–881.
64.
Tajeripour, F., Kabir, E., Sheikhi, A., 2007. Fabric Defect Detection Using Modified Local Binary Patterns. In: Proceedings of the International Conference on Computational Intelligence and Multimedia Applications, pp. 261–267.
65.
Tamura, H., Mori, S., Yamawaki, T., 1978. Textural Features Corresponding to Visual Perception. IEEE Transactions on Systems, Man, and Cybernetics 8, 460–473.
66.
Theodoridis, S., Koutroumbas, K., 2009. Pattern Recognition, Fourth Edition, Academic Press, CA.
163
67.
Tuceryan, M., and Jain, A.K., 1998. Texture Analysis, in: Chen, C.H., Pau, L.F., and Wang, P.S.P. (Eds.): The Handbook of Pattern Recognition and Computer Vision (2nd Edition), World Scientific Publishing Company, pp. 207–248.
68.
Turner, M., 1986. Texture discrimination by Gabor functions. Biological Cybernetics 55, 71–82.
69.
Wang, Z., Bowik, C., 2002. A Universal Image Quality Index, IEEE Signal Processing Letters 9, 81–84.
70.
Weyl, H., 1952. Symmetry, Princeton University Press, New Jersey.
71.
Xie, P., Guan, S.U., 2000. A golden-template self-generating method for patterned wafer inspection. Machine Vision and Applications 12, 149–156.
72.
Yu, Z., Wong, H.S., Wang, H., 2007. Graph-Based Consensus Clustering for Class Discovery from Gene Expression Data. Bioinformatics 23 (21), 2888– 2896.
164
