Signal processing and pattern recognition with soft computing

Proceedings of the IEEE

Volumn 89, Issue 9, 2001, Pages 1297-1316

  Suzuki, Yukinori ^a   Saga, Sato ^a   Maeda, Junji ^a  

^a MURORAN INSTITUTE OF TECHNOLOGY   (Japan)

Author keywords

ART2; Cps detection

Indexed keywords

EID: 0012603541     PISSN: 00189219     EISSN: None     Source Type: Journal    
DOI: 10.1109/5.949486     Document Type: Article

References (105)

1. L. A. Zadeh, "What is soft computing," Soft CompuL, vol. 1, no. 1, pp. 1-2, 1997.
2. P. P. Bonissone, "Soft computing: The convergence of emerging reasoning technologies," Soft CompuL, voî. 1, no. 1, pp. 6-18, 1997.
3. [31 L. A. Zadeh, "From computing with numbers to computing with words-From manipulation of measurements to manipulation of perceptions," IEEE Trans. Circuits Syst. I, vol. 46, pp. 105-119, Jan. 1999.
4. A. G. Constantinides, S. Haykin, Y. H. Hu, J. H. Hwang, S. Katagiri, S. Kung, and T. Poggio, "Introduction: Neural networks for signal processing," IEEE Trans. Signal Processing, vol. 45, pp. 2637-2638, Nov. I997.
5. H. Watanabe, T. Yamaguchi, and S. Katagiri, "Discriminative metric design for robust pattern recognition," IEEE Trans. Signal Processing, vol. 45, pp. 2655-2662, Nov. 1997.
6. M. Schuster and K. K. Paliwal, "Bidirectional recurrent neural networks," IEEE Trans. Signal Processing, vol. 45, pp, 2673-2681, Nov. 1997.
7. [7 j S. K. Halgamuge, "Self-evolving neural networks for rule-based data processing," IEEE Trans. Signal Processing, vol. 45, pp. 2766-2773, Nov. 1997.
8. S. Y. Kung and J. N. Hwang, "Neural networks for intelligent multimedia processing." Proc. IEEE, vol. 86, pp. 1244-1272, June 1998.
9. [91 A. K. Jain and J. Mao, "Guest editorial: Special issue on artificial neural networks and statistical pattern recognition," IEEE Trans. Neural Networks, vol. 8. Jan. 1997.
10. Y. Suzuki, S. Sakamoto, Y. Kurimoio, and J. Maeda, "Detection of characteristic points using a MART," Trans. Inst. Elect. Eng. Jpn., vol. 121-C. no. 3. pp. 594-600, 2001.
11. Y. Yao, W. J. Freeman, B. Burke, and Q. Yang. "Pattern recognition by a distributed neural network: An industrial application," Neural Networks, vol. 4, pp. 103-121, 1991.
12. S. B. Serpico, L. Brazzone, and F, Roli, "An experimental comparison of neural and statistical nonparametric algorithms for supervised classification of remote-sensing images." Pattern Recognit. Let!..\ol. 17, pp. 1131-1134, 1996.
13. D. Valentin, H. Abdi, A. J. O'Toole, and G. W. Cottrell, "Connectionist models of face processing: A survey," Pattern Recognit., vol. 27, no. 9, pp. 1209-1230, 1994.
14. S. Cho, "Neural-network classifiers for unconstrained handwritten numbers," IEEE Trans. Neural Networks, vol. 8, pp. 43-53. Jan. 1997.
15. M. Laviolette and j. W. Seaman. "The efficacy of fuzzy representations of uncertainty," IEEE Trans. Fitzzv Sv.it.. vol. 2, pp. 4-15, Feb. 1994.
16. [ ! 6] D. Dubois and H. Prade, "Fuzzy sets-A convenient fiction for modeling vagueness and possibility," IEEE Irans, f'uzzv Syst., vol. 2, pp. 16-21, Feb. 1994.
17. W. Predrycz and F. Gomide, An Introduction to Fuzzy Sets. Cambridge, MA: MIT Press, 1998.
18. [ 181 W. Pedrycz, "Special issue on fuzzy set technology in pattern recognition,"' Pattern Recogr.it. Lett., vol. 17, 1996.
19. M. Grabisch, "The representation of importance and interaction of features by fuzzy measures," Pattern Recognil. Lett., vol. 17, pp. 567-575, "1996.
20. P. D. Gader, M. A. Mohamed, and J. M. Keller, "Fusion of handwritten word classifier," Pattern Recognil. Lett., vol. 17, pp. 577-584, 1996.
21. [21j H. Bandemer, "Specifying fuzzy data from grey-tone pictures for pattern recognition," Pattern Recognil. Lett., vol. 17, pp. 585-592, 1996.
22. L. A. Zadeh, "Fuzzy sets," Inform. Contr., vol. 8, pp. 338-353, 1965.
23. W. Pedrycz, "Fuzzy set in pattern recognition: Methodology and methods," Pattern Recognit., vol. 23, no. 1/2, pp. 121-146, 1990.
24. [24J E. Binaghi, M. A. Mohamed, and J. M. Keller, "A fuzzy set-based accuracy assessment of soft classification," Pattern Recognit. Lett., vol. 20, pp. 935-948, 1999.
25. L. A. Zadeh, "Outline of a new approach to the analysis of complex systems and'decision processes," IEEE Trims. Syst., Man, Cybem., vol. SMC-3, no. 1, 1973.
26. M. Sakakazu, Foundation and Application of Fuzzy Set Theory. Tokyo, Japan: Morikita, 1989.
27. [271 S. M. Bhandarkar, Y. Zhang, and W. D. Potter, "An edge detection technique using genetic algorithm-based optimization," Pattern Recognit, vol. 27, no. 9, pp. 1159-1180, 1994.
28. P. Audrey and P. Tarroux, "Unsupervised image segmentation using a distributed genetic algorithm," Pattern Recognit., vol. 27, no. 5, pp. 659-673, 1994.
29. T. Back, U. Hammel, and H. P. Schwefel, "Evolutionary computation: Comments on history and current state," IEEE Trans. Evol. Comput., vol. 1, pp. 3-17, Feb. 1997.
30. D. N. Chun and H. S. Yang, "Robust image segmentation using genetic algorithm with a fuzzy measure," Pattern Recognit., vol. 29, no. 7, pp. 1195-1211, 1996'.
31. M. Sarkar, B. Yegnanarayana, and D. Khemani, "A clustering algorithm using an evolutionary programming-based approach," Pattern Recognit. Lett., vol. 18, pp. 975-986, 1997.
32. A. Toet and W. P. Hajema, ''Genetic contour matching," Pattern Recognit., vol. 16, pp. 849-865, 1995.
33. J. Piper, "Genetic algorithm for applying constraints in chromosome classification." Pattern Recognil. Lett., vol. 16, pp. 857-864, 1995.
34. D. Kilpatrick and P. R. Johnston, "Origin of the electrocardiogram," IEEE Eng. Med. Biol, pp. 479 186, Aug.-Sept. 1994.
35. [351 C. B. Mason and J. E. Davis, Cardiovascular Circuit Care. New York: Van Nostrand Reinhold, 1987.
36. M. Okajima, Computer Diagnosis of Electrocardiogram. Tokyo, Japan: Xakayarna Shoten, 1989.
37. [37j J. Pan and W. J. Tompkins, "A real time QRS detection algorithm," IEEE Trans. Biomed. Eng., vol. BME-32, pp. 230-236, Mar. 1985.
38. [381 P. S. Hamilton and W. J. Tompkins, "Quantitative investigation of QRS detection rules using MIT/BIH arrhythmia database," IEEE Trans. Biomed. Eng., vol. BME-33, pp. 1157-1165, Dec. 1986.
39. Q. Xue, Y. H. Hu, and W. J. Tompkins, "Neutral network based adaptive matched filter for QRS detection," IEEE Trans. Biomed. Eng., vol. 39, pp. 317-329, Apr. 1992.
40. G. M. Friesen, T. C. Jannett, M. A. Jadailah, S. L. Yates, S. R. Quint, and H. T. Nagle, "A comparison of the noise sensitivity of nine QRS detection algorithms," IEEE Trans. Biomed. En;j., vol. 37, pp. 85-98, Jan. 1990.
41. E. Czogala and J. Leski, "Application of entropy and energy measures cf fuzziness to processing of ECG signal," Fuzzy Sets Syst., vol. 97. pp. 9-18, 1998.
42. [421 P. Trahanias and E. Skordalakis, "Bottom-up approach to the ECG pattern-recognition problem," Med. Biol. Eng. Cornpui., vol. 27, pp. 221-229, 1989.
43. J. K. Udupa and I. S. N. Murthy, "Syntactic approach to ECG rhythm analysis," IEEE Trans. Bionied. Eng., vol BME-27, pp. 370-375, July 1980.
44. J. S. Sahambi, S. N. Tandon, and R. K. P. Bhatta, "Using wavelet transforms for ECG characterization," IEEE Eng. Med. Bio'. Mag., pp. 77-82, Jan.-Feb. 1997.
45. [451 L. C. Zheng and C. Tai, "Detection of ECG characteristic points using wavelet transforms," IEEE Trans, Biomeii. Eng., vol. 42, pp. 21-28, Jan. 1995.
46. R. Silipo and C. Marches!, "Artificial neural networks for automatic ECC analysis," IEEE Trans. Signal Processing, vol. 46, pp. 1417-1425, May 1998.
47. A. Koski, "Primitive coding of structurai ECG features," Pattern Kecognit. Lett., vol. 17, pp. 1215-1222. !996.
48. M. Kundu, M. Nasipuri, and D. K. Basil, "A knowledge-based approach to ECG interpretation using fuzzy logic," IEEE Trans. Syst., Man, Cybern. B, vol. 28, pp. 237-243, Apr. 1998.
49. "Knowledge-based ECG interpretation: A critical review." Pattern Recognil., vol. 32, pp. 351-373, 2000.
50. T. Stamkopoulos. K. Diamataras, N. Maglaveras, and M. Strintzis, "ECG analysis using nonlinear PCA neural networks for ischemia detection," IEEE Trans. Signal Processing, vol. 46, pp. 3058-3067, Nov. 1998.
51. Y. Suzuki and K. Ono, "Personal computer system for ECG ST-segment recognition based on neural networks," Med. Biol. Comput., vol. 30, pp. 2-8, 1992.
52. [52J Y. Suzuki, "Self-organizing QRS-wave recognition in ECG using neural networks," IEEE Trans. Neural Networks, vol. 6, pp. 1469-1477, Nov. 1995.
53. G. A. Carpenter and S. Grossberg, "ART2: Self-organization of stable category recognition codes for analog input palierns," Appl. Opt., vol. 26, pp. 4919-4930, 1987.
54. M. Fernandez-Delgado and S. B. Arnenerio, "MART: A multichannel ART-based neural network," IEEE Trans. Neural Networks, vol. 9, pp. 139-149, Jan. 1998.
55. The CSE Working Party, "Recommendations for measurement of standard in quantitative electrocardiography," Eur. Heart J., vol. 6, pp. 815-825, 1985.
56. K. Itakura, K. Sato, G. Deguchi, Y. Ichihara, H. Matsumoto, and H. Eguchi, "Development of a roof-logging system by rockbolt drilling," Trans. Ins!. Min. Metall, pt. A, vol. 106, pp. 118-123, 1997.
57. K. Itakura, K. Sato, G. Deguchi, Y. Ichihara, H. Matsumoto, and H. Eguchi, "Estimation of the 3-D geostructure of roof rock in mines using a mechanical data logging system for rock-bolt drilling," in Proc. 4th Int. Symp. Mining Mechanization and Automation, 1997, Paper V2, pp. 65-74.
58. [581 K. Itakura, K. Sato, G. Deguchi, Y. Ichihara, and H. Matsumoto, "Visualization system for roof rock using the mechanical data of roofbolter" (in Japanese). J. Min. Maier. Process. Inst. Jpn.. vol. 115, no. 13, pp. 1033-1039, 1999.
59. J. A. Freeman and D. M. Skapura, Neural Networks Algorithms, Applications and Programming Techniques. Reading, MA: AddisonWelsey, 1991.
60. R. Shao, "Incremental recognition in gesture-based and syntax-directed diagram editors," in l.VTERCHI '93, Apr. 1993, pp. 95-100.
61. T. Baudel, "A mark-based interaction paradigm for free-hand drawing," in VIST '94, Nov. pp. 185-192.
62. E. Saund and T. P. Vloran, "A perceptually-supported sketch editor," in VIST '94, Nov. pp. 175-184.
63. [631 M. D. Gross and E. Y. Do, "Ambiguous intentions: A paper-like interface for creative design," U 1ST '96, pp. 183-192, Nov. 1996.
64. [64; T. Igarashi, S. Matsuoka, S. Kawachiya, and H. Tanaka, "Interactive beautification: A technique for rapid geometric design," in VIST '97, Oct. 1997, pp. ',05-114.
65. S. Saga and H. Makino, "Fuzzy spline interpolation and its application to on-line freehand curve identification," in Proc. 2nd SEEK Int. Conf. Fuzzy Systems, San Francisco, CA, Mar. 1993, pp. 1183-1190.
66. S. Saga, H. Makino, and J. Sasaki, "A method for modeling freehand curves-The fuzzy spline interpolation" (in Japanese), IEICE Trans., vol. J77-D-I1, pp. 'l610-1619, Aug. 1994.
67. S. Saga, H. Makino, and J. Sasaki, "The fuzzy spline curve identifier" (in Japanese), IEICE Trans., vol. J77-D-II, pp. 1620-1629, Aug. 1994.
68. S. Saga and J. Sasaki, "A freehand CAD drawing interface based on the fuzzy spline curve identifier" (in Japanese), IPSJ Trans., vol. 36, pp. 338-350, Feb. i995.
69. S. Saga, "A freehand interface for computer aided drawing systems based on the fuzzy spline curve identifier," in P roc. 1995 IEEE Int. Conf. Systems, Man ant! Cybernetics, Vancouver, BC, Canada, Oct. 1995, pp. 2754-2759.
70. [70, S. Saga and N. Seino, "Trainable fuzzy spline curve identifier using a neural network," in P roc. Int. Workshop on Soft Computing in Industry '96, Muroran, Japan, Apr. 1996. pp. 41-46.
71. S. Saga and S. Mori, "Trainable freehand curve identifier with a fuzzy neural network," in Proc. 5th Ear. Congr. Intelligent Technique:; and Soft Computing, Aachen, Germany, Sept. 1997, pp. 127-131.
72. S. Saga and T. Ohkawa, "Refinement of fuzziness generator for the freehand curve identifier FSCI," in Proc. 2nd IEEE Int. Conf. Intelligent Processing Svstems, Gold Coast, Australia, Aug. 1998, pp. 323-329.
73. S. Saga, S. Mon, and T. Yamaguchi, "Training of the freehand curve identifier FSCi using h fuzzy neural network," in Proc. Int. Workshop on Soft Computing in Industry '99, Muroran, Japan, June pp. 281-286.
74. G. Farin, Curves and Surfaces for Computer Aided Geometric Design: A Practical Guide. New York: Academic, 1988.
75. L. A. Zadeh, "Fuzzy sets as a basis for a theory of possibility," Fuzzy Sets Syst., vol. 1, no. 1, pp. 3-28, 1978.
76. [76) R. M. Haralick and L. G. Shapiro, "Image segmentation techniques," Cornput. Vis. Graph. Image Process., vol. 29. pp. 100-132. 1985.
77. N. R. Pal and S. K. Pal, "A review on image segmentation techniques," Pattern Recognit., vol. 26, no. 9, pp. 1277-1294, 1993.
78. T. R. Reed and j. M. H. du Buf, "A review of recent texture segmentation and feature extraction techniques," CVGIP: Image Understand., vol. 57, pp. 359-372, 1993.
79. "Special issue - Neural networks for computer vision applications," Int. J. Neural Syst., vol. 8, no. 1, 1997.
80. R. Chellappa, k. Fukushima, A. K. Katsaggelos, S.-Y. Kung, Y. LeCttn, N. M. Nasrabadi, and T. A. Poggio. Eds., "Special issue on applications of artificial neural networks to image processing," in IEEE Trans. Image Processing, Aug. 1998, vol. 7.
81. L. A. Zadeh. "Fuzzy sets and their applications to classification and clastering," in Classification and Clustering, J. van Ryzin, Ed. New York: Academic, 1977, pp. 251-299.
82. B. B. Bezdeck. Pattern Recognition with Fuzzy Objective Function Algorithms. New York: Plenum, 1981.
83. [831 "Special issue on fuzzy set technology in pattern recognition," Pattern Recognit. Lett., vol. 17. no. 6, 1996.
84. A. Baraldi and P. Bionda, "A survey of fuzzy clustering algorithms for pattern recognition," IEEE Trans. Syst., Man, Cybern. B, vol. 29, pp. 778-801, 1999.
85. A. P. Pentland, "Fractal-based description of natural scenes," IEEE Trans. Pattern Anal. Machine Inteli, vol. PAMI-6, no. 6, pp. 661-674. 1984.
86. S. Peleg, J. Naor, R. Hardy, and D. Avnir, "Multiple resolution texture analysis and classification," IEEE Trans. Pattern Anal. Machine Intell., vol. PAMI-6, no. 4, pp. 518-523, 1984.
87. J. M. Keller, S. Chen, and R. Crownover, "Texture description and segmentation through fractal geometry," Comput, Vis. Graph. Image Process., vol. 45, pp. 150-166, 1989.
88. N. Sarkar and B. B. Chaudhuri, "An efficient approach to estimate fractal dimension of texture images," Pattern Recognit., vol. 25, no. 9, pp. 1035-1041, 1992.
89. "An efficient differential box-counting approach to compute fractal dimension of image," IEEE Trans. Syst., Man., Cybem., vol. 24, pp. 115-120, Jan. 1994.
90. J. Maeda and H. Nanjyo, "Segmentation of natural images by the integration of fractal dimension and edge information" (in Japanese), 1E1CE Trans., vol. J-78-D-II, no. 11, pp. 1726-1729, 1995.
91. V. V. Ahn, J. Maeda, T. Ishizaka, Y. Suzuki, and Q. Tieng, "Twodimensional fractal segmentation of natural images," Proc. Int. Conf. Image Analysis and Processing, vol. I, pp. 287-294, 1997.
92. J. Maeda, S. Novianto, V. V. Anh, Q. Tieng, and Y. Suzuki, "Accurate estimation of local fractal dimension in natural images using Fourierwavelet transform" (in Japanese), JEICE Trans., vol. J-82-A, no. 5, pp. 750-754, 1999.
93. S. Novianto, L. Guimaraes, J. Maeda, and V. V. Anh, "Multiwindowed approach to the optimum estimation of the local fractal dimension for natural image segmentation," in Proc. IEEE Int. Conf. Image Processing, vol. 3~ pp. 222-226.
94. J. M. Keller and Y. B. Seo, "Local fractal geometric features for image segmentation," Int. j. Imag. Syst. Technol., vol. 2, pp. 267-284, 1990.
95. [951 J. Maeda, S. Novianto, S. Saga, Y. Suzuki, and V. V. Ann, "Rough and accurate segmentation of natural images using fuzzy regiongrowing algorithm,'' in Proc. IEEE In:. Conf. Image Processing, vol. 3, pp. 227-231.
96. [961 J. Maeda. C. Ishikawa, S. Novianto, N. Tadehara, and Y. Suzuki, "Rough and accurate segmentation of natural color images using fuzzy region-growing algorithm," in Proc. 15th Int. Conf. Pattern Recognition, vol. 5, 2000, pp. 642-645.
97. j. Maeda, V. V. Ann, T. ishizaka, and Y. Suzuki, "Integration of local fractal dimension and boundary edge iu segmenting natural images," in Proc. IEEE Int. Conf. Image Processing, vol. 1, 1996, pp. 845-848.
98. S. G. Kong and B. Kosko, "Image coding with fuzzy image segmentation," in Proc. IEEE Int. Coif Fuzzy Systems, 1992, pp. 212-220.
99. A. Steude! and VI. Glesner, "Image coding with fuzzy region-growing segmentation," in Proc. IEEE Int. Conf. Image Processing, vol. 2, 1996. pp. 955-958.
100. [ 100] B. B. Mandelbrot, The f'racial Geometry of Nature. San Francisco, CA: Freeman, 1982.
101. P. Brodatz, Texture: A Photographic Album for Artists and Designers, New York: Dover, 1966.
102. J. Maeda, T. lizawa, T. Ishizaka, C. Ishikawa, and Y. Suzuki, "Segmentation of natural images using anisotropic diffusion and linking of boundary edges," Pattern Kecognil., vol. 31, no. 12, pp. 1993- 1998.
103. Y. Suzuki, S. Ovaska, R. Roy, T. Furuhashi, and Y. Dote, Eels., Soft Computing in Industrial Applications. London, U.K.: Springer, 1999.
104. D. A. Bernstein, E. J. Roy, T. K. Srull, and C. D. Wickens, Psychology. Boston, MA: Houghton Mifflin, 1988.
105. [1051 S. J. Ovaska, Y. Dote, T. Furuhashi, A. Kamiya, and H. F. VanLandingham, "Fusion of soft computing and hard computing techniques: A review of applications," in Proc. IEEESMC'99, pp. I-370-I-375.