Image processing and mathematical morphology: Fundamentals and applications

Image Processing and Mathematical Morphology: Fundamentals and Applications

Volumn , Issue , 2009, Pages 1-417

  Shih, Frank Y ^a  

^a NEW JERSEY INSTITUTE OF TECHNOLOGY   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

EID: 85056966931     PISSN: None     EISSN: None     Source Type: Book    
DOI: None     Document Type: Book

References (326)

1. Angulo, J. and Serra, J., “Automatic analysis of DNA microarray images using mathematical morphology,” Bioinformatics, vol. 19, no. 5, pp. 553–562, Mar. 2003.
2. Damera-Venkata, N., Kite, T. D., Geisler, W. S., Evans, B. L., and Bovik, A. C., “Image quality assessment based on a degradation model,” IEEE Trans. Image Processing, vol. 9, no. 4, pp. 636–650, Apr. 2000.
3. Dineen, G. P., “Programming pattern recognition,” Proc. Western Joint Computer Conference, Los Angeles, CA, pp. 94–100, Mar. 1–3, 1955.
4. Dougherty, E. R., Mathematical Morphology in Image Processing, Miami: CRC Press, 1993.
5. Giardina, C. and Dougherty, E., Morphological Methods in Image and Signal Processing, Prentice-Hall, Englewood Cliffs, NJ, 1988.
6. Golay, M. J. E., 1969, “Hexagonal parallel pattern transformations,” IEEE Trans. Computers, vol. 18, no. 8, pp. 733–740, Aug. 1969.
7. Goutsias, J. and Heijmans, H. J., Mathematical Morphology, IOS Press, Amsterdam, the Netherlands, 2000.
8. Haralick, R. M., Sternberg, S. R., and Zhuang, X., Image analysis using mathematical morphology, IEEE Trans. Pattern Analysis and Machine Intelligence, vol. 9, no. 4, pp. 532–550, July 1987.
9. Heckbert, P., “Color image quantization for frame buffer display,” ACM SIGGRAPH Computer Graphics, vol. 16, no. 3, pp. 297–307, July 1982.
10. Huang, T. S., “PCM picture transmission,” IEEE Spectrum, vol. 2, no. 12, pp. 57–63, Dec. 1965.
11. Kirsch, R. A.”Experiments in processing life motion with a digital computer,” Proc. Eastern Joint Computer Conference, pp. 221–229, 1957.
12. Maragos, P. and Schafer, R., “Morphological filters—Part II: Their relations to median, order-statistics, and stack filters,” IEEE Trans. Acoustics, Speech, Signal Processing, vol. 35, no. 8, pp. 1170–1184, Aug. 1987.
13. Matheron, G., Random Sets and Integral Geometry, John Wiley, New York, 1975.
14. Minkowski, H., “Volumen und oberflache,” Mathematical Annals, vol. 57, pp. 447–495, 1903.
15. Moore, G. A., “Automatic sensing and computer process for the quantitative analysis of micrographs and equivalued subjects,” in C. George, R. S. Ledley, D. K. Pollock, and A. Rosenfeld (Eds.), Pictorial Pattern Recognition, Thompson Book Co., Durank, OK, pp. 275–326, 1968.
16. Nomura, S., Yamanaka, K., Katai, O., Kawakami, H., and Shiose, T., “A novel adaptive morphological approach for degraded character image segmentation,” Pattern Recognition, vol. 38, no. 11, pp. 1961–1975, Nov. 2005.
17. Oliveira, M. A. and Leite, N. J., “A multiscale directional operator and morphological tools for reconnecting broken ridges in fingerprint images,” Pattern Recognition, vol. 41, no. 1, pp. 367–377, Jan. 2008.
18. Preston, K. Jr., “Machine techniques for automatic identification of binucleate lymphocyte,” Proc. Int. Conf. Medical Electronics, D.C., 1961.
19. Said, E. H., Nassar, D. E. M., Fahmy, G., and Ammar, H. H., “Teeth segmentation in digitized dental X-ray films using mathematical morphology,” IEEE Trans. Information Forensics and Security, vol. 1, no. 2, pp. 178–189, June 2006.
20. Schonfeld, D. and Goutsias, J., “Optimal morphological pattern restoration from noisy binary images,” IEEE Trans. Pattern Analysis and Machine Intelligence, vol. 13, no. 1, pp. 14–29, Jan. 1991.
21. Serra, J., Image Analysis and Mathematical Morphology, Academic Press, New York, 1982.
22. Serra, J., “Introduction to mathematical morphology,” Computer Vision, Graphics, and Image Processing, vol. 35, no. 3, pp. 283–305, Sep. 1986.
23. Serra, J., Image Analysis and Mathematical Morphology, Vol. 2: Theoretical Advances, Academic Press, New York, 1988.
24. Shih, F. Y. and Mitchell, O. R., “Threshold decomposition of grayscale morphology into binary morphology,” IEEE Trans. Pattern Analysis and Machine Intelligence, vol. 11, no. 1, pp. 31–42, Jan. 1989.
25. Shih, F. Y. and Mitchell, O. R., ‘’Decomposition of gray scale morphological structuring elements,” Pattern Recognition, vol. 24, no. 3, pp. 195–203, March 1991.
26. Sivakumar, K. and Goutsias, J., “Morphologically constrained GRFs: applications to texture synthesis and analysis,” IEEE Trans. Pattern Analysis and Machine Intelligence, vol. 21, no. 2, pp. 99–113, Feb. 1999.
27. Soille, P. and Pesaresi, M., “Advances in mathematical morphology applied to geoscience and remote sensing,” IEEE Trans. Geoscience and Remote Sensing, vol. 40, no. 9, pp. 2042–2055, Sep. 2002.
28. Trahanias, P. E., “An approach to QRS complex detection using mathematical morphology,” IEEE Trans. Biomedical Engineering, vol. 40, no. 2, pp. 201–205, Feb. 1993.
29. Xia, Y., D. Feng, and Zhao, R., “Morphology-based multifractal estimation for texture segmentation,” IEEE Trans. Image Processing, vol. 15, no. 3, pp. 614–623, Mar. 2006.
30. Bloomberg, D. and Maragos, P., “Generalized hit-miss operations,” in P. Gader (Ed.), Image Algebra and Morphological Image Processing 1998, Proceedings, vol. 1350, SPIE, San Diego, CA, USA, 1990, pp. 116–128.
31. Haralick, R. M., Sternberg, S. R., and Zhuang, X., “Image analysis using mathematical morphology,” IEEE Trans. Pattern Analysis and Machine Intelligence, vol. 9, no. 4, pp. 532–550, July 1987.
32. Heijmans, H. J. A. M. and Ronse, C., “The algebraic basis of mathematical morphology—I: dilations and erosions,” Computer Vision, Graphics and Image Processing: Image Understanding, vol. 50, no. 3, pp. 245–295, June 1990.
33. Heijmans, H. J. A. M. and Ronse, C., “The algebraic basis of mathematical morphology—II: openings and closings,” Computer Vision, Graphics and Image Processing: Image Understanding, vol. 54, no. 1, pp. 74–97, July 1991.
34. Khosravi, M. and Schafer, R. W., “Template matching based on a grayscale hit-or-miss transform,” IEEE Trans. Image Processing, vol. 5, no. 6, pp. 1060–1066, June 1996.
35. Matheron, G., Random Sets and Integral Geometry, John Wiley, New York, 1975.
36. Naegel, B., Passat, N., and Ronse, C., “Grey-level hit-or-miss transforms—Part I: Unified theory,” Pattern Recognition, vol. 40, no. 2, pp. 635–647, Feb. 2007a.
37. Naegel, B., Passat, N., and Ronse, C., “Grey-level hit-or-miss transforms—Part II: Application to angiographic image processing,” Pattern Recognition, vol. 40, no. 2, pp. 648–658, Feb. 2007b.
38. Raducanu, B. and Grana, M., “A grayscale hit-or-miss transform based on level sets,” Proc. IEEE Intl. Conf. Image Processing, Vancouver, BC, Canada, pp. 931–933, 2000.
39. Schaefer, R. and Casasent, D., “Nonlinear optical hit-miss transform for detection,” Applied Optics, vol. 34, no. 20, pp. 3869–3882, July 1995.
40. Serra, J., Image Analysis and Mathematical Morphology, Academic Press, New York, 1982.
41. Aptoula, E. and Lefèvre, S., “A comparative study on multivariate mathematical morphology,” Pattern Recognition, vol. 40, no. 11, pp. 2914–2929, Nov. 2007.
42. Burgeth, B., Bruhn, A., Didas, S., Weickert, J., and Welk, M., “Morphology for matrix data: Ordering versus PDE-based approach,” Image and Vision Computing, vol. 25, no. 4, pp. 496–511, Apr. 2007.
43. Fitch, J. P., Coyle, E. J., and Gallagher, N. C., “Threshold decomposition of multidimensional ranked order operations,” IEEE Trans. Circuits and Systems, vol. 32, no. 5, pp. 445–450, May 1985.
44. Haralick, R. M., Sternberg, S. R., and Zhuang, X., Image analysis using mathematical morphology, IEEE Trans. Pattern Analysis and Machine Intelligence, vol. 9, no. 4, pp. 532–550, July 1987.
45. Heijmans, H. J. A. M., “Theoretical aspects of gray-level morphology,” IEEE Trans. Pattern Analysis and Machine Intelligence, vol. 13, no. 6, pp. 568–582, June 1991.
46. Serra, J., Image Analysis and Mathematical Morphology, Academic Press, New York, 1982.
47. Shih, F. Y. and Mitchell, O. R., Threshold decomposition of grayscale morphology into binary morphology, IEEE Trans. Pattern Analysis and Machine Intelligence, vol. 11, no. 1, pp. 31–42, Jan. 1989.
48. Sternberg, S. R., “Grayscale morphology,” Computer Vision, Graphics, and Image Processing, vol. 35, no. 3, pp. 333–355, Sep. 1986.
49. Blum, H., “A transformation for extracting new descriptors of shape,” in Walthen Dunn (Ed.), Models for the Perception of Speech and Visual Forms, Proceedings of Meeting held on Nov. 1964, MIT Press, MA, 1967, pp. 362–380.
50. Feehs, R. J. and Arce, G. R., “Multidimensional morphological edge detection,” Proc. SPIE Visual Comm. and Image Processing II, vol. 845, pp. 285–292, 1987.
51. Gonzalez, R. and Woods, R., Digital Image Processing, Prentice-Hall, third edition, 2007.
52. Jang, B. and Chin, R. T., “Analysis of thinning algorithms using mathematical morphology,” IEEE Trans. Pattern Analysis and Machine Intelligence, vol. 12, no. 6, pp. 541–551, June 1990.
53. Ji, L. and Piper J., “Fast homotopy-preserving skeletons using mathematical morphology,” IEEE Trans. Pattern Analysis and Machine Intelligence, vol. 14, no. 6, pp. 653–664, June 1992.
54. Lee, J. S., Haralick, R. M., and Shapiro, L. G., “Morphologic edge detection,” IEEE Trans. Robotics and Automation, vol. 3, no. 2, pp. 142–156, Apr. 1987.
55. Maragos, P. A. and Schafer, R. W., “Morphological skeleton representation and coding of binary images,” IEEE Trans. Acoustics, Speech, and Signal Processing, vol. 34, no. 5, pp. 1228–1244, Oct. 1986.
56. Meyer, F. “Skeletons in digital spaces,” in J. Serra (Ed.), Image Analysis and Mathematical Morphology, vol. 2, Academic Press, New York, pp. 257–296, 1988.
57. Moran, C. J., “A morphological transformation for sharpening edges of features before segmentation,” Compute Vision, Graphics and Image Processing, vol. 49, no. 1, pp. 85–94, Jan. 1990.
58. Serra, J., Image Analysis and Mathematical Morphology, Academic Press, New York, 1982.
59. Shih, F. Y. and Pu, C. C., “A skeletonization algorithm by maxima tracking on Euclidean distance transform,” Pattern Recognition, vol. 28, no. 3, pp. 331–341, Mar. 1995.
60. Shih, F. Y. and Wu, Y., “The efficient algorithms for achieving Euclidean distance transformation,” IEEE Trans. Image Processing, vol. 13, no. 8, pp. 1078–1091, Aug. 2004.
61. Agam, G. and Dinstein, I., “Regulated morphological operations,” Pattern Recognition, vol. 32, no. 6, pp. 947–971, June 1999.
62. Brodatz, P., Textures: A Photographic Album for Artists and Designers, Dover Publications, New York, 1966.
63. Chatzis, V. and Pitas, I., “A generalized fuzzy mathematical morphology and its application in robust 2-D and 3-D object representation,” IEEE Trans. Image Processing, vol. 9, no. 10, pp. 1798–1810, Oct. 2000.
64. Danielsson, P. E., “A new shape factor,” Comput. Graphics Image Processing, vol. 7, no. 2, pp. 292–299, Apr. 1978.
65. David, H., Order Statistics, Wiley, New York, 1981.
66. Destival, I., “Mathematical morphology applied to remote sensing,” Acta Astronaut., vol. 13, no. 6/7, pp. 371–385, June–July 1986.
67. Gasteratos, A., Andreadis, I., and Tsalides, P., “A new hardware structure for implementation of soft morphological filters,” Computer Analysis of Images and Patterns, Lecture Notes in Computer Science, Springer, vol. 1296, pp. 488–494, 1997.
68. Gasteratos, A., Andreadis, I., and Tsalides, P., “Fuzzy soft mathematical morphology,” IEE Proc. Vision, Image and Signal Processing, vol. 145, no. 1, pp. 41–49, Feb. 1998.
69. Giardina, C. and Dougherty, E., Morphological Methods in Image and Signal Processing, Prentice-Hall, Englewood Cliffs, NJ, 1988.
70. Giles, R., “Lukasiewicz logic and fuzzy theory,” Intl. Journal Man-Machine Stud., vol. 8, no. 3, pp. 313–327, 1976.
71. Großert, S., Koppen, M., and Nickolay, B. A., “New approach to fuzzy morphology based on fuzzy integral and its application in image processing,” Proc. Intl. Conf. Pattern Recognition, vol. 2, pp. 625–630, Aug. 1996.
72. Hamid, M. S., Harvey, N. R., and Marshall, S., “Genetic algorithm optimization of multidimensional grayscale soft morphological filters with applications in film archive restoration,” IEEE Trans. Circuits and Systems for Video Technology, vol. 13, no. 5, pp. 406–416, May 2003.
73. Haralick, R., Zhuang, X., Lin, C., and Lee, J., “The digital morphological sampling theorem,” IEEE Trans. Acoust. Speech, Signal Processing, vol. 37, no. 12, pp. 2067–2090, Dec. 1989.
74. Heijmans, H. J. A. M., “A new class of alternating sequential filters,” in Proc. IEEE Workshop on Nonlinear Signal and Image Processing, vol. 2, pp. 30–33, 1995.
75. Heijmans, H. J. A. M., “Composing morphological filters,” IEEE Trans. Image Processing, vol. 6, no. 5, pp. 713–723, May 1997.
76. Ko, S.-J., Morales, A., and Lee, K.-H., “Fast recursive algorithms for morphological operators based on the basis matrix representation,” IEEE Trans. Image Processing, vol. 5, no. 6, pp. 1073–1077, June 1996.
77. Koskinen, L., Astola, J. T., and Neuvo, Y. A., “Soft morphological filters,” in D. Gader and E. R. Dougherty (Eds.), Proc. SPIE, vol. 1568, Image Algebra and Morphological Image Processing II, pp. 262–270, July 1991.
78. Kuosmanen, P. and Astola, J., “Soft morphological filtering,” Journal of Mathematical Imaging and Vision, vol. 5, no. 3, pp. 231–262, Sep. 1995.
79. Li, W. and Coat, V. H., “Composite morphological filters in multiresolution morphological decomposition,” Proc. IEE Workshop on Image Processing and Applications, no. 410, pp. 752–756, July 1995.
80. Maragos, P. and Schafer, R., “Morphological filters—Part I: Their set-theoric analysis and relations to linear shift-invariant filters,” IEEE Trans. Acoustics, Speech, and Signal Processing, vol. 35, no. 8, pp. 1153–1169, Aug. 1987a.
81. Maragos, P. and Schafer, R., “Morphological filters—Part II: Their relations to median, order-statistics, and stack filters,” IEEE Trans. Acoustics, Speech, and Signal Processing, vol. 35, no. 8, pp. 1170–1184, Aug. 1987b.
82. Morales, A., Acharya, R., and Ko, S.-J., “Morphological pyramids with alternating sequential filters,” IEEE Trans. Image Processing, vol. 4, no. 7, pp. 965–977, July 1995.
83. Nadadur, D. and Haralick, R. M., “Recursive binary dilation and erosion using digital line structuring elements in arbitrary orientations,” IEEE Trans. Image Processing, vol. 9, no. 5, pp. 749–759, May 2000.
84. Pei, S., Lai, C., and Shih, F. Y., “An efficient class of alternating sequential filters in morphology,” Graphical Models and Image Processing, vol. 59, no. 2, pp. 109–116, Mar. 1997.
85. Pei, S., Lai, C., and Shih, F. Y., “Recursive order-statistic soft morphological filters,” IEE Proceedings Vision, Image and Signal Processing, vol. 145, no. 5, pp. 333–342, Oct. 1998.
86. Preteux, F., Laval-Jeantet, A. M., Roger, B., and Laval-Jeantet, M. H., “New prospects in C.T. image processing via mathematical morphology,” Eur. J. Radiol., vol. 5, no. 4, pp. 313–317, 1985.
87. Pu, C. C. and Shih, F. Y., “Threshold decomposition of gray-scale soft morphology into binary soft morphology,” Graphical Model and Image Processing, vol. 57, no. 6, pp. 522–526, Nov. 1995.
88. Schonfeld, D. and Goutsias, J., “Optical morphological pattern restoration from noisy binary image,” IEEE Trans. Pattern Anal. Mach. Intelligence, vol. 13, no. 1, pp. 14–29, Jan. 1991.
89. Serra, J., Image Analysis and Mathematical Morphology, Academic Press, New York, 1982.
90. Shih, F. Y., Chuang, C., and Gaddipati, V., “A modified regulated morphological corner detector,” Pattern Recognition Letters, vol. 26, no. 7, pp. 931–937, June 2005.
91. Shih, F. Y., King, C. T., and Pu, C. C., “Pipeline architectures for recursive morphological operations,” IEEE Trans. Image Processing, vol. 4, no. 1, pp. 11–18, Jan. 1995.
92. Shih, F. Y. and Mitchell, O. R., “Threshold decomposition of gray-scale morphology into binary morphology,” IEEE Trans. Pattern Analysis and Machine Intelligence, vol. 11, no. 1, pp. 31–42, Jan. 1989.
93. Shih, F. Y. and Mitchell, O. R., “A mathematical morphology approach to Euclidean distance transformation,” IEEE Trans. Image Processing, vol. 1, no. 2, pp. 197–204, Apr. 1992.
94. Shih, F. Y. and Pu, C. C., “Analysis of the properties of soft morphological filtering using threshold decomposition,” IEEE Trans. Signal Processing, vol. 43, no. 2, pp. 539–544, Feb. 1995.
95. Shih, F. Y. and Puttagunta, P., “Recursive soft morphological filters,” IEEE Trans. Image Processing, vol. 4, no. 7, pp. 1027–1032, July 1995.
96. Sinha, D. and Dougherty, E. R., “Fuzzy mathematical morphology,” Journal of Visual Communication and Image Representation, vol. 3, no. 3, pp. 286–302, Sep. 1992.
97. Sinha, D. and Dougherty, E. R, “A general axiomatic theory of intrinsically fuzzy mathematical morphologies,” IEEE Trans. Fuzzy Systems, vol. 3, no. 4, pp. 389–403, Nov. 1995.
98. Smith, S. W., The Scientist and Engineer’s Guide to Digital Signal Processing, California Technical Pub., 1997.
99. Soille, P., “On morphological operators based on rank filters,” Pattern Recognition, vol. 35, no. 2, pp. 527–535, Feb. 2002.
100. Sternberg, S. R., “Grayscale morphology,” Computer Vision, Graphics, and Image Processing, vol. 35, pp. 333–355, Sep. 1986.
101. Stevenson, R. L. and Arce, G. R., “Morphological filters: Statistics and further syntactic properties,” IEEE Trans. Circuits and Systems, vol. 34, no. 11, pp. 1292–1305, Nov. 1987.
102. Strauss, O. and Comby, F., “Variable structuring element based fuzzy morphological operations for single viewpoint omnidirectional images,” Pattern Recognition, vol. 40, no. 12, pp. 3578–3596, Dec. 2007.
103. Tian, X.-H., Li, Q.-H., and Yan, S.-W., “Regulated morphological operations with weighted structuring element,” Proc. Intl. Conf. Machine Learning and Cybernetics, pp. 768–771, Nov. 2002.
104. Wendt, P. D., Coyle, E. J., and Gallagher, N. C., “Stack filters,” IEEE Trans. Acoust., Speech, Signal Processing, vol. 34, no. 4, pp. 898–911, Aug. 1986.
105. Wirth, M. A. and Nikitenko, D., “Applications of fuzzy morphology to contrast enhancement,” Proc. Annual Meeting of the North American Fuzzy Information Processing Society, pp. 355–360, June 2005.
106. Yang, G.-Q., Guo, Y.-Y., and Jiang, L.-H., “Edge detection based on adaptive fuzzy morphological neural network,” Proc. Intl. Conf. Machine Learning and Cybernetics, pp. 3725–3728, Aug. 2006.
107. Yli-Harja, O., Astola, J., and Neuvo, Y., “Analysis of the properties of median and weighted median filters using threshold logic and stack filter representation,” IEEE Trans. Signal Processing, vol. 39, no. 2, pp. 395–409, Feb. 1991.
108. You, X. and Crebbin, G., “A robust adaptive estimation for filtering noise images,” IEEE Trans. Image Processing, vol. 4, no. 5, pp. 693–699, May 1995.
109. Yu, P. T. and Liao, W. H., “Weighted order statistics filters—Their classification, some properties, and conversion algorithms,” IEEE Trans. Signal Processing, vol. 42, no. 10, pp. 2678–2691, Oct. 1994.
110. Zadeh, L. A., “Fuzzy sets,” Information Control, vol. 8, no. 3, pp. 338–353, June 1965.
111. Zadeh, L. A., “Theory of fuzzy sets,” in Encyclopedia of Computer Science and Technology in J. Belzer, A. Holzman, and A. Kent (Eds.), Dekker, New York, 1977.
112. Blum, H., “A transformation for extracting new descriptors of shape,” Proc. of Symposium on Models for the Perception of Speech and Visual Forms, Boston, MA, MIT Press, Nov. 1964.
113. Borgefors, G., “Distance transformations in arbitrary dimensions,” Computer Vision, Graphics, and Image Processing, vol. 27, no. 3, pp. 321–345, Sep. 1984.
114. Borgefors, G., “Distance transformations in digital images,” Computer Vision, Graphics, and Image Processing, vol. 34, no. 3, pp. 344–371, June 1986.
115. Coeurjolly, D. and Montanvert, A., “Optimal separable algorithms to compute the reverse Euclidean distance transformation and discrete medial axis in arbitrary dimension,” IEEE Trans. Pattern Analysis and Machine Intelligence, vol. 29, no. 3, pp. 437–448, March 2007.
116. Cuisenaire, O., “Locally adaptable mathematical morphology using distance transformations,” Pattern Recognition, vol. 39, no. 3, pp. 405–416, March 2006.
117. Cuisenaire, O. and Macq, B., “Fast Euclidean distance transformation by propagation using multiple neighborhoods,” Computer Vision and Image Understanding, vol. 76, no. 2, pp. 163–172, Nov. 1999.
118. Danielsson, P. E., “A new shape factor,” Computer Graphics and Image Processing, vol. 7, no. 2, pp. 292–299, Apr. 1978.
119. Danielsson, P. E., “Euclidean distance mapping,” Computer Graphics Image Processing, vol. 14, no. 3, pp. 227–248, Nov. 1980.
120. Datta, A. and Soundaralakshmi, S., “Constant-time algorithm for the Euclidean distance transform on reconfigurable meshes,” Journal of Parallel and Distributed Computing, vol. 61, no. 10, pp. 1439–1455, Oct. 2001.
121. 2 based on sufficient propagation,” Computer Vision and Image Understanding, vol. 69, no. 1, pp. 106–116, Jan. 1998.
122. Fabbri, R., Costa, L., Torelli, J., and Bruno, O., “2D Euclidean distance transform algorithms: A comparative survey,” ACM Computing Surveys, vol. 40, no. 1, pp. 2:1–2:44, Feb. 2008.
123. Hilditch, J., “Linear skeletons from square cupboards,” in Meltzer and D. Michie (Eds), Machine Intelligence, vol. 4, American Elsevier Publishiers Co., pp. 403–420, 1969.
124. Huang, C. T. and Mitchell, O. R., “A Euclidean distance transform using grayscale morphology decomposition,” IEEE Trans. Pattern Analysis and Machine Intelligence, vol. 16, no. 4, pp. 443–448, Apr. 1994.
125. Lantuejoul, C., “Skeletonization in quantitative metallography,” in R. M. Haralick and J. C. Simon (Eds), Issues in Digital Image Processing, Sijthoff & Noordhoff Publishers, Maryland, pp. 107–135, 1980.
126. Maurer, C. R., Rensheng, Q., and Raghavan, V., “A linear time algorithm for computing exact Euclidean distance transforms of binary images in arbitrary dimensions,” IEEE Trans. Pattern Analysis and Machine Intelligence, vol. 25, no. 2, pp. 265–270, Feb. 2003.
127. Pei, S.-C., Lai, C.-L., and Shih, F. Y., “A morphological approach to shortest path planning for rotating objects,” Pattern Recognition, vol. 31, no. 8, pp. 1127–1138, Aug. 1998.
128. Rosenfeld, A. and Pfaltz, J. L., “Sequential operations in digital picture processing,” J. ACM, vol. 13, no. 4, pp. 471–494, Oct. 1966.
129. Rosenfeld, A. and Kak, A. C., Digital Picture Processing, Academic Press, New York, 1982.
130. Saito, T. and Toriwaki, J.-I., “New algorithms for Euclidean distance transformation of an n-dimensional digitized picture with applications,” Pattern Recognition, vol. 27, no. 11, pp. 1551–1565, Nov. 1994.
131. Serra, J., Image Analysis and Mathematical Morphology, Academic Press, New York, 1982.
132. Shih, F. Y. and Liu, J., “Size-invariant four-scan Euclidean distance transformation,” Pattern Recognition, vol. 31, no. 11, pp. 1761–1766, Nov. 1998.
133. Shih, F. Y. and Mitchell, O. R., “Skeletonization and distance transformation by grayscale morphology,” Proc. of SPIE Symposium on Automated Inspection and High Speed Vision Architectures, Cambridge, MA, pp. 80–86, Nov. 1987.
134. Shih, F. Y. and Mitchell, O. R., “Threshold decomposition of grayscale morphology into binary morphology,” IEEE Trans. Pattern Analysis and Machine Intelligence, vol. 11, no. 1, pp. 31–42, Jan. 1989.
135. Shih, F. Y. and Mitchell, O. R., “Decomposition of grayscale morphological structuring elements,” Pattern Recognition, vol. 24, no. 3, pp. 195–203, March 1991.
136. Shih, F. Y. and Mitchell, O. R., “A mathematical morphology approach to Euclidean distance transformation,” IEEE Trans. Image Processing, vol. 1, no. 2, pp. 197–204, April 1992.
137. Shih, F. Y. and Wu, H., “Optimization on Euclidean distance transformation using grayscale morphology,” Journal of Visual Communication and Image Representation, vol. 3, no. 2, pp. 104–114, June 1992.
138. Shih, F. Y. and Wu, Y., ‘’Three-dimensional Euclidean distance transformation and its application to shortest path planning,” Pattern Recognition, vol. 37, no. 1, pp. 79–92, Jan. 2004a.
139. Shih, F. Y. and Wu, Y., ‘’Fast Euclidean distance transformation in two scans using a 3 × 3 neighborhood,” Computer Vision and Image Understanding, vol. 93, no. 2, pp. 195–205, Feb. 2004b.
140. Shih, F. Y. and Wu, Y., ‘’The efficient algorithms for achieving Euclidean distance transformation,” IEEE Trans. Image Processing, vol. 13, no. 8, pp. 1078–1091, Aug. 2004c.
141. Shih, F. Y. and Wu, Y., ‘’Decomposition of arbitrarily grayscale morphological structuring elements,” Pattern Recognition, vol. 38, no. 12, pp. 2323–2332, Dec. 2005.
142. Toriwaki, J. and Yokoi, S., “Distance transformations and skeletons of digitized pictures with applications,” in L. N. Kanal and A. Rosenfeld (Eds), Progress in Pattern Recognition, North-Holland Publishers, pp. 187–264, 1981.
143. Vincent, L., “Exact Euclidean distance function by chain propagations,” Proc. IEEE Computer Vision and Pattern Recognition, Hawaii, pp. 520–525, 1991.
144. Vossepoel, A. M., “A note on distance transformations in digital images,” Computer Vision, Graphics, and Image Processing, vol. 43, no. 1, pp. 88–97, July 1988.
145. Xu, D. and Li, H., “Euclidean distance transform of digital images in arbitrary dimensions,” in Y. Zhuang et al. (Eds), Lecture Notes in Computer Science, Springer, LNCS 4261, pp. 72–79, 2006
146. Agam, G. and Dinstein, I., “Regulated morphological operations,” Pattern Recognition, vol. 32, no. 6, pp. 947–971, June 1999.
147. Bouaynaya, N. and Schonfeld, D., “Theoretical foundations of spatially-variant mathematical morphology. Part II: Gray-level images,” IEEE Trans. Pattern Analysis and Machine Intelligence, vol. 30, no. 5, pp. 837–850, May 2008.
148. Cheng, F. and Venetsanopoulos, A. N., “An adaptive morphological filter for image processing,” IEEE Trans. Image Processing, vol. 1, no. 4, pp. 533–539, Oct. 1992.
149. Danielsson, P. E., “A new shape factor,” Computer Graphics and Image Processing, vol. 7, no. 2, pp. 292–299, Apr. 1978.
150. Dinesh, R. and Guru, D. S., “Corner detection using morphological skeleton: An efficient and nonparametric approach,” Lecture Notes in Computer Science, Springer, Berlin/Heidelberg, pp. 752–760, 2006.
151. Gauch, J. M., “Image segmentation and analysis via multiscale gradient watershed hierarchies,” IEEE Trans. Image Processing, vol. 8, no. 1, pp. 69–79, Jan. 1999.
152. Gu, C. and Lee, M.-C., “Semiautomatic segmentation and tracking of semantic video objects,” IEEE Trans. Image Processing, vol. 8, no. 5, pp. 572–584, Sep. 1998.
153. Kitchen, L. and Rosenfeld, A., “Gray-level corner detection,” Pattern Recognition Letters, vol. 1, no. 2, pp. 95–102, Dec. 1982.
154. Laganiere, R., “A morphological operator for corner detection,” Pattern Recognition, vol. 31, no. 11, pp. 1643–1652, Nov. 1998.
155. Lee, K.-J. and Bien, Z., “A gray-level corner detector using fuzzy logic,” Pattern Recognition Letters, vol. 17, no. 9, pp. 939–950, Aug. 1996.
156. Lin, R.-S., Chu, C.-H., and Hsueh, Y.-C., “A modified morphological corner detector,” Pattern Recognition Letters, vol. 19, no. 3–4, pp. 279–286, Mar. 1998.
157. Liu, S.-M., Lin, W.-C., and Liang, C.-C., “An iterative edge linking algorithm with noise removal capability,” Proc. International Conference on Pattern Recognition, vol. 2, pp. 1120–1122, 1988.
158. Nalwa, V. S. and Pauchon, E., “Edgel aggregation and edge description,” Comput. Vision, Graphics, Image Processing, vol. 40, no. 1, pp. 79–94, Jan. 1987.
159. Nevatia, R., “Locating objects boundaries in textured environments,” IEEE Trans. Computers, vol. 25, no. 11, pp. 1170–1175, Nov. 1976.
160. Rosenfeld, A. and Kak, A. C., Digital Picture Processing, vol. 2, Academic Press, New York, 1982.
161. Russ, J. C., The Image Processing Handbook, CRC Press, Boca Raton, FL, 1992.
162. Shih, F. Y., “Object representation and recognition using mathematical morphology model,” International Journal of Systems Integration, vol. 1, no. 2, pp. 235–256, Aug. 1991.
163. Shih, F. Y. and Cheng, S., “Adaptive mathematical morphology for edge linking,” Information Sciences, vol. 167, no. 1–4, pp. 9–21, Dec. 2004.
164. Shih, F. Y., Chuang, C., and Gaddipati, V., “A modified regulated morphological corner detector,” Pattern Recognition Letters, vol. 26, no. 7, pp. 931–937, June 2005.
165. Singh, A. and Shneier, M., “Gray level corner detection a generalization and a robust real time implementation,” Comput. Vision Graphics Image Processing, vol. 51, no. 1, pp. 54–69, July 1990.
166. Sobania, A., Paul J., and Evans, O., “Morphological corner detector using paired triangular structuring elements,” Pattern Recognition, vol. 38, no. 7, pp. 1087–1098, July 2005.
167. Tian, X.-H., Li, Q.-H., and Yan, S.-W., “Regulated morphological operations with weighted structuring element,” Proc. Int. Conf. Machine Learning Cybernat., pp. 768–771, Nov. 2002.
168. Tsai, D.-M., Hou, H.-T., and Su, H.-J., “Boundary-based corner detection using eigenvalues of covariance matrices,” Pattern Recognition Letters, vol. 20, no. 1, pp. 31–40, Jan. 1999.
169. Verly, J. G. and Delanoy, R. L., “Adaptive mathematical morphology for range imagery,” IEEE Trans. Image Processing, vol. 2, no. 2, pp. 272–275, Apr. 1993.
170. Vincent, L. and Soille, P., “Watersheds in digital spaces: An efficient algorithm based on immersion simulations,” IEEE Trans. on Pattern Analysis and Machine Intelligence, vol. 13, no. 6, pp. 583–598, June 1991.
171. Wang, D., “Unsupervised video segmentation based on watersheds and temporal tracking,” IEEE Trans. Circuits and System for Video Technology, vol. 8, no. 5, pp. 539–546, Sep. 1998.
172. Yun, I. D., Park, S. H., and Lee, S. U., “Color image segmentation based on 3D clustering: Morphological approach,” Pattern Recognition, vol. 31, no. 8, pp. 1061–1076, Aug. 1998.
173. Zana, F. and Klein, J.-C., “Segmentation of vessel-like patterns using mathematical morphology and curvature evaluation,” IEEE Trans. Image Processing, vol. 10, no. 7, pp. 1010–1019, July 2001.
174. Zhang, X., and Zhao, D., “A morphological algorithm for detecting dominant points on digital curves,” Proc. SPIE Nonlinear Image Processing, 2424, pp. 372–383, 1995.
175. Zheng, Z., Wang, H., and Teoh, E., “Analysis of gray level corner detection,” Pattern Recognition Letters, vol. 20, no. 2, pp. 149–162, Feb. 1999.
176. American National Standards Institute (ANSI), Dimensioning and Tolerancing, ANSI Standard Y14.5M, ASME, New York, 1982.
177. Arcelli, C. and Sanniti di Baja, G., “A one-pass two-operation process to detect the skeletal pixels on the 4-distance transform,” IEEE Trans. Pattern Analysis and Machine Intelligence, vol. 11, no. 4, pp. 411–414, Apr. 1989.
178. Blum, H., “A transformation for extracting new descriptors of shape,” in W. Dunn (Ed), Models for the Perception of Speech and Visual Forms, Proc. of Meeting held November 1964, MIT Press, Massachusetts, pp. 362–380, 1967.
179. Bouaynaya, N., Charif-Chefchaouni, M., and Schonfeld, D., “Spatially-variant morphological restoration and skeleton representation,” IEEE Trans. Image Processing, vol. 15, no. 11, pp. 3579–3591, Nov. 2006.
180. Bronskill, J. and Venetsanopoulos, A., “Multidimensional shape description and recognition using mathematical morphology,” Journal of Intell. and Robotics Sys., vol. 1, no. 2, pp. 117–143, June 1988.
181. Dougherty, E. and Pelz, J., “Morphological granulometric and analysis of electro-photographic images—size distribution statistics for process control,” Optical Engineering, vol. 30, no. 4, pp. 438–445, Apr. 1991.
182. Fu, K. S., Syntactic Pattern Recognition and Applications, Prentice-Hall, 1982.
183. Ghosh, P. K., “A mathematical model for shape description using Minkowski operators,” Computer Vision, Graphics, and Image Processing, vol. 44, no. 3, pp. 239–269, Dec. 1988.
184. Goutsias, J. and Schonfeld, D., “Morphological representation of discrete and binary images,” IEEE Trans. Signal Processing, vol. 39, no. 6, pp. 1369–1379, June 1991.
185. Jalba, A. C. Wilkinson, M. H. F., and Roerdink, J. B. T. M., “Shape representation and recognition through morphological curvature scale spaces,” IEEE Trans. Image Processing, vol. 15, no. 2, pp. 331–341, Feb. 2006.
186. Jang, B. K. and Chin, R. T., “Analysis of thinning algorithm using mathematical morphology,” IEEE Trans. Pattern Analysis and Machine Intelligence, vol. 12, no. 6, pp. 541–551, June 1990.
187. Jang, B. K. and Chin, R. T., “One-pass parallel thinning: Analysis, property, and quantitative evaluation,” IEEE Trans. Pattern Analysis and Machine Intelligence, vol. 14, no. 11, pp. 1129–1140, Nov. 1992.
188. Kresch, R. and Malah, D., “Skeleton-based morphological coding of binary images,” IEEE Trans. Image Processing, vol. 7, no. 10, pp. 1387–1399, Oct. 1998.
189. Kwok, P. C. K., “A thinning algorithm by contour generation,” Comm. ACM, vol. 31, no. 11, pp. 1314–1324, Nov. 1988.
190. Loncaric, S. and Dhawan, A. P., “A morphological signature transform for shape description,” Pattern Recognition, vol. 26, no. 7, pp. 1029–1037, July 1993.
191. Margos, P. A. and Schafer, R. W., “Morphological skeleton representation and coding of binary images,” IEEE Trans. Acoustics, Speech and Signal Processing, vol. 34, no. 5, pp. 1228–1244, Oct. 1986.
192. Maragos, P. A., “A representation theory for morphological image and signal processing,” IEEE Trans. Pattern Analysis and Machine Intelligence, vol. 11, no. 6, pp. 586–599, June 1989a.
193. Maragos, P. A., “Pattern spectrum and multiscale shape representation,” IEEE Trans. Patt. Anal. Mach. Intell., vol. 11, no. 7, pp. 701–716, July 1989b.
194. Matheron, G., Random Sets and Integral Geometry, New York: Wiley, 1975.
195. Niblack, C. W., Capson, D. W., and Gibbons, P. B., “Generating skeletons and centerlines from the MA transform,” Proc. Intl. Conf. Pattern Recognition, Atlantic City, New Jersey, pp. 881–885, June 1990.
196. Naccache, N. J. and Shinghal, R., “SPTA: A proposed algorithm for thinning binary patterns,” IEEE Trans. Systems, Man and Cybernetics, vol. 14, no. 3, pp. 409–418, May 1984.
197. O’Gorman, L. “K × K thinning,” Computer Vision, Graphics and Image Processing, vol. 51, no. 2, pp. 195–215, Aug. 1990.
198. Rossignac, J. R. and Requicha, A. A. G., “Offsetting operations in solid modelling,” Production Automation Project, Univ. Rochester, Rochester, NY Tech. Memo, 53, June 1985.
199. Serra, J., Image Analysis and Mathematical Morphology, New York: Academic, 1982.
200. Shih, F. Y., “Object representation and recognition using mathematical morphology model,” Inter. Journal of Systems Integration, vol. 1, no. 2, pp. 235–256, Aug. 1991.
201. Shih, F. Y. and Gaddipati, V., “Geometric modeling and representation based on sweep mathematical morphology,” Information Sciences, vol. 171, no. 3, pp. 213–231, March 2005.
202. Shih, F. Y. and Pu, C. C., “Medial axis transformation with single-pixel and connectivity preservation using Euclidean distance computation,” Proc. IEEE Intl. Conf. on Pattern Recognition, Atlantic City, New Jersey, pp. 723–725, 1990.
203. Shih, F. Y. and Pu, C. C., “Morphological shape description using geometric spectrum on multidimensional binary images,” Pattern Recognition, vol. 25, no. 9, pp. 921–928, Sep. 1992.
204. Shih, F. Y. and Pu, C. C., “A skeletonization algorithm by maxima tracking on Euclidean distance transform,” Pattern Recognition, vol. 28, no. 3, pp. 331–341, March 1995.
205. Trahanias, P., “Binary shape recognition using the morphological skeleton transform,” Pattern Recognition, vol. 25, no. 11, pp. 1277–288, Nov. 1992.
206. Xu, J., “Morphological representation of 2-D binary shapes using rectangular components,” Pattern Recognition, vol. 34, no. 2, pp. 277–286, Feb. 2001.
207. Xu, J., “A generalized discrete morphological skeleton transform with multiple structuring elements for the extraction of structural shape components,” IEEE Trans. Image Processing, vol. 12, no. 12, pp. 1677–1686, Dec. 2003.
208. Yu, L. and Wang, R., “Shape representation based on mathematical morphology,” Pattern Recognition Letters, vol. 26, no. 9, pp. 1354–1362, July 2005.
209. Zhang, T. Y. and Suen, C. Y., “A fast thinning algorithm for thinning digital patterns,” Comm. ACM, vol. 27, no. 3, pp. 236–239, Mar. 1984.
210. Anelli, G., Broggi, A., and Destri, G., “Decomposition of arbitrarily shaped binary morphological structuring elements using genetic algorithms,” IEEE Trans. Pattern Analysis and Machine Intelligence, vol. 20, no. 2, pp. 217–224, Feb. 1998.
211. Camps, O. I., Kanungo, T., and Haralick, R. M., “Grayscale structuring element decomposition,” IEEE Trans. Image Processing, vol. 5, no. 1, pp. 111–120, Jan. 1996.
212. Gader, P. D., “Separable decompositions and approximations of grayscale morphological templates,” CVGIP: Image Understanding, vol. 53, no. 3, pp. 288–296, May 1991.
213. Haralick, R. M., Sternberg, S. R., and Zhuang, X., “Image analysis using mathematical morphology,” IEEE Trans. Pattern Analysis and Machine Intelligence, vol. 9, no. 7, pp. 532–550, July 1987.
214. Hashimoto, R. F. and Barrera, J., “A note on Park and Chin’s algorithm,” IEEE Trans. Pattern Analysis and Machine Intelligence, vol. 24, no. 1, pp. 139–144, Jan. 2002.
215. Herrera, F., Lozano, M., and Verdegay, J. L., “Applying genetic algorithms in fuzzy optimization problems,” Fuzzy Systems and Artificial Intelligence, vol. 3, no. 1, pp. 39–52, Jan. 1994.
216. Ho, S.-Y., Chen, H.-M., and Shu, L.-S., “Solving large knowledge base partitioning problems using the intelligent genetic algorithm,” Proc. Inter. Conf. Genetic and Evolutionary Computation, pp. 1567–1572, 1999.
217. Holland, J. H., Adaptation in Natural and Artificial Systems, The University of Michigan Press, Ann Arbor, MI, 1975.
218. Holland, J. H., Adaptation in Natural and Artificial System: An Introductory Analysis with Applications to Biology, Control, and Artificial Intelligence, MIT Press, Cambridge, MA, 1992.
219. Park, H. and Chin, R. T., “Optimal decomposition of convex morphological structuring elements for 4-connected parallel array processors,” IEEE Trans. Pattern Analysis and Machine Intelligence, vol. 16, no. 3, pp. 304–313, March 1994.
220. Park, H. and Chin, R. T., “Decomposition of arbitrarily shaped morphological structuring elements,” IEEE Trans. Pattern Analysis and Machine Intelligence, vol. 17, no. 1, pp. 2–15, Jan. 1995.
221. Richardson, C. H. and Schafer, R. W., “A lower bound for structuring element decompositions,” IEEE Trans. Pattern Analysis and Machine Intelligence, vol. 13, no. 4, pp. 365–369, April 1991.
222. Serra, J., Image Analysis and Mathematical Morphology, Academic Press, New York, 1982.
223. Shih, F. Y. and Mitchell, O. R., “Threshold decomposition of grayscale morphology into binary morphology,” IEEE Trans. Pattern Analysis and Machine Intelligence, vol. 11, no. 1, pp. 31–42, Jan. 1989.
224. Shih, F. Y. and Mitchell, O. R., “Decomposition of grayscale morphological structuring elements,” Pattern Recognition, vol. 24, no. 3, pp. 195–203, Mar. 1991.
225. Shih, F. Y. and Mitchell, O. R., “A mathematical morphology approach to Euclidean distance transformation,” IEEE Trans. Image Processing, vol. 1, no. 2, pp. 197–204, April 1992.
226. Shih, F. Y. and Puttagunta, P., “Recursive soft morphological filters,” IEEE Trans. Image Processing, vol. 4, no. 7, pp. 1027–1032, July 1995.
227. Shih, F. Y. and Wu, Hong, “Decomposition of geometric-shaped structuring elements using morphological transformations on binary image,” Pattern Recognition, vol. 25, no. 10, pp. 1097–1106, 1992.
228. Sussner, P., Pardalos, P. M., and Ritter, G. X., “On integer programming approaches for morphological template decomposition problems in computer vision,” Journal of Combinatorial Optimization, vol. 1, no. 2, pp. 165–178, 1997.
229. Sussner, P. and Ritter, G. X., “Decomposition of grayscale morphological templates using the rank method,” IEEE Trans. Pattern Analysis and Machine Intelligence, vol. 19, no. 6, pp. 649–658, June 1997.
230. Sussner, P. and Ritter, G. X., “Rank-based decomposition of morphological templates,” IEEE Trans. Image Processing, vol. 19, no. 6, pp. 1420–1430, June 2000.
231. Tang, K.-S., Man, K.-F., Liu, Z.-F., and Kwong, S., “Minimal fuzzy memberships and rules using hierarchical genetic algorithms,” IEEE Trans. Industrial Electronics, vol. 45, no. 1, pp. 162–169, Jan. 1998.
232. Yang, H.-T. and Lee, S.-J., “Decomposition of morphological structuring elements with integer linear programming,” IEE Proc. Vision, Image and Signal Processing, vol. 152, no. 2, pp. 148–154, April 2005.
233. Zhuang, X. and Haralick, R. M., “Morphological structuring element decomposition,” Computer Vision, Graphics, and Image Processing, vol. 35, no. 3, pp. 370–382, Sep. 1986.
234. Armstrong, W. W. and Gecsei, J., “Adaptation algorithms for binary tree networks,” IEEE Trans. Syst., Man, Cybern., vol. 9, no. 5, pp. 276–285, May 1979.
235. Athas, W. L. and Seitz, C. L., “Multicomputers: Message-passing concurrent computers,” IEEE Trans. Computers, vol. 21, no. 8, pp. 9–24, Aug. 1988.
236. Duff, M. J. B., “Parallel processors for digital image processing,” in P. Stucki (Ed), Advances in Digital Image Processing, Plenum Press, London, pp. 265–279, 1979.
237. Fitch, J. P., Coyle, E. J., and Gallager, N. C., “Threshold decomposition of multidimensional ranked order operations,” IEEE Trans. Circuits and Systems, vol. 32, no. 5, pp. 445–450, May 1985.
238. Fukushima, K., “Cognitron: a self-organizing multilayered neural network,” Biological Cybernetics, vol. 20, no. 3–4, pp. 121–136, Sep. 1975.
239. Fukushima, K., “Neocognitron: a neural network model for a mechanism of visual pattern recognition,” IEEE Trans. Syst., Man, Cybern., vol. 13, no. 5, pp. 826–834, Sep. 1983.
240. Fukushima, K., “Neocognitron: a hierarchical neural network capable of visual pattern recognition,” Neural Network, vol. 1, no. 2, pp. 119–130, April 1988.
241. Gerritsen, F. A. and Aardema, L. G., “Design and use of DIP-1: A fast flexible and dynamically microprogrammable image processor,” Pattern Recognition, vol. 14, no. 1–6, pp. 319–330, 1981.
242. Golay, M. J. E., “Hexagonal parallel pattern transformations,” IEEE Trans. Computers, vol. 18, no. 8, pp. 733–740, Aug. 1969.
243. Graham, D. and Norgren, P. E., “The Diff3 analyzer: A parallel/serial Golay image processor,” in Onoe, Preston, and Rosenfeld (Eds), Real Time Medical Image Processing, Plenum, London, pp. 163–182, 1980.
244. Handley, J. C., “Bit vector architecture for computational mathematical morphology,” IEEE Trans. Image Processing, vol. 12, no. 2, pp. 153–158, Feb. 2003.
245. Handley, J. C., “Minimal-memory bit-vector architecture for computational mathematical morphology using subspace projections,” IEEE Trans. Image Processing, vol. 14, no. 8, pp. 1088–1095, Aug. 2005.
246. Huang, S. C. and Huang, Y. F., “Bounds on the number of hidden neurons in multilayer perceptrons,” IEEE Trans. Neural Networks, vol. 2, no. 1, pp. 47–55, Jan. 1991.
247. Hwang, K., “Advanced parallel processing with supercomputer architectures,” Proc. IEEE, vol. 75, no. 10, pp. 1348–1379, Oct. 1987.
248. King, C. T. and Ni, L. M., “Large-grain pipelining on hypercube multiprocessors,” Proc. Third ACM Conf. Hypercube Concurrent Computers and Applications, pp. 1583–1591, 1988.
249. Klein, J. C. and Serra, J., “The texture analyzer,” Journal of Microscopy, vol. 95, pp. 349–356, 1977.
250. Krishnapuram, R. and Chen, L. F., “Implementation of parallel thinning algorithms using recurrent neural networks,” IEEE Trans. Neural Networks, vol. 4, no.1, pp. 142–147, Jan. 1993.
251. Kruse, B., “Design and implementation of a picture processor,” Science and Technology Dissertations, no. 13, University of Linkoeping, Linkoeping, Sweden, 1977.
252. Lippmann, R. P., “An introduction to computing with neural nets,” IEEE ASSP Magazine, vol. 42, no. 4, pp. 4–22, Apr. 1987.
253. Lougheed, R. M. and McCubbrey, D. L. “The cytocomputer: A practical pipelined image processor,” Proc. IEEE Annual Symp. Computer Architecture, La Baule, France, pp. 271–278, 1980.
254. Louverdis, G. and Andreadis, I., “Design and implementation of a fuzzy hardware structure for morphological color image processing,” IEEE Trans. Circuits and Systems for Video Technology, vol. 13, no. 3, pp. 277–288, March 2003.
255. Martin, T., “Acoustic recognition of a limited vocabulary in continuous speech,” Ph.D. Thesis, Dept. Electrical Engineering Univ. Pennsylvania, 1970.
256. Minsky, M. L. and Papert, S. A., Perceptrons, MIT Press, Cambridge, MA, 1969.
257. Moh, J. and Shih, F. Y., “A general purpose model for image operations based on multilayer perceptrons,” Pattern Recognition, vol. 28, no. 7, pp. 1083–1090, July 1995.
258. Rosenblatt, F., Principles of Neurodynamics, New York, Spartan, 1962.
259. Rumelhart, D. E., Hinton, G. E., and Williams, R. J., “Learning representations by back-propagating errors,” Nature, vol. 323, pp. 533–536, Oct. 1986.
260. Shih, F. Y. and Mitchell, O. R., “Threshold decomposition of grayscale morphology into binary morphology,” IEEE Trans. Pattern Analysis and Machine Intelligence, vol. 11, no. 1, pp. 31–42, Jan. 1989.
261. Shih, F. Y. and Moh, J., “Implementing morphological operations using programmable neural networks,” Pattern Recognition, vol. 25, no. 1, pp. 89–99, Jan. 1992.
262. Sternberg, S. R., “Biomedical image processing,” Computer, vol. 16, no. 1, pp. 22–34, Jan. 1983.
263. Vidal, J. J., “Implementing neural nets with programmable logic,” IEEE Trans. ASSP, vol. 36, no. 7, pp. 1180–1190, July 1988.
264. Wendt, P. D., Coyle, E. J., and Gallagher, N. C., “Stack filters,” IEEE Trans. Acoust., Speech, Signal Processing, vol. 34, no. 6, pp. 898–911, Aug. 1986.
265. Banon, G. and Barrera, J., “Decomposition of mappings between complete lattices by mathematical morphology, Part I: General lattices,” Signal Processing, vol. 30, no. 3, pp. 299–327, Feb. 1993.
266. Beucher, S., Blosseville, J. M., and Lenoir, F., “Traffic spatial measurements using video image processing,” in Proc. SPIE. Intelligent Robots and Computer Vision, vol. 848, pp. 648–655, Nov. 1987.
267. Blackmore, D., Leu, M. C., and Shih, F. Y., “Analysis and modeling of deformed swept volumes,” Computer Aided Design, vol. 26, no. 4, pp. 315–326, Apr. 1994.
268. Bouaynaya, N. and Schonfeld, D., “Theoretical foundations of spatially variant mathematical morphology—Part II: Gray-level images,” IEEE Trans. Pattern Analysis and Machine Intelligence, vol. 30, no. 5, pp. 837–850, May 2008.
269. Bouaynaya, N., Charif-Chefchaouni, M., and Schonfeld, D., “Spatially variant mathematical morphology: A geometry-based theory,” Tech. Rep. MCL-TR-2005-01, Multimedia Communications Lab., Univ. Illinois at Chicago, 2004.
270. Bouaynaya, N., Charif-Chefchaouni, M., and Schonfeld, D., “Spatially variant morphological restoration and skeleton representation,” IEEE Trans. Image Processing, vol. 15, no. 11, pp. 3579–3591, Nov. 2006.
271. Bouaynaya, N. and Schonfeld, D., “Theoretical foundations of spatially variant mathematical morphology—Part II: Gray-level images,” IEEE Trans. Pattern Analysis and Machine Intelligence, vol. 30, no. 5, pp. 837–850, May 2008.
272. Brooks, R. A., “Symbolic reasoning among three-dimensional models and two-dimensional images,” Artificial Intelligence, vol. 17, no. 1–3, pp. 285–348, Aug. 1981.
273. Chen, C. S., Wu, J. L., and Hung, Y. P., “Statistical analysis of space-varying morphological openings with flat structuring elements,” IEEE Trans. Signal Processing, vol. 44, no. 4, pp. 1010–1014, Apr. 1996.
274. Chen, C. S., Wu, J. L., and Hung, Y. P., “Theoretical aspects of vertically invariant gray-level morphological operators and their application on adaptive signal and image filtering,” IEEE Trans. Signal Processing, vol. 47, no. 4, pp. 1049–1060, Apr. 1999.
275. Cooper, D., Elliott, H., Cohen, F., and Symosek, P., “Stochastic boundary estimation and object recognition,” Computer Graphics Image Process, vol. 12, no. 4, pp. 326–356, Apr. 1980.
276. Cuisenaire, O., “Locally adaptable mathematical morphology using distance trans-formations,” Pattern Recognition, vol. 39, no. 3, pp. 405–416, March 2006.
277. Debayle, J. and Pinoli, J. C., “General adaptive neighborhood image processing—Part I: Introduction and theoretical aspects,” Journal of Math. Imaging and Vision, vol. 25, no. 2, pp. 245–266, Sep. 2006a.
278. Debayle, J. and Pinoli, J. C., “General adaptive neighborhood image processing— Part II: Practical application examples,” Journal of Math. Imaging and Vision, vol. 25, no. 2, pp. 267–284, Sep. 2006b.
279. Eichel, P. H., Delp, E. J., Koral, K., and Buda, A. J., “A method for a fully automatic definition of coronary arterial edges from cineangiograms,” IEEE Trans. Medical Imaging, vol. 7, no. 4, pp. 313–320, Dec. 1988.
280. Farag, A. A. and Delp, E. J., “Edge linking by sequential search,” Pattern Recognition, vol. 28, no. 5, pp. 611–633, May 1995.
281. Foley, J., van Dam, A., Feiner, S., and Hughes, J., Computer Graphics: Principles and Practice, 2nd edition, MA: Addison-Wesley, 1995.
282. Fu, K. S., Syntactic Pattern Recognition and Applications, NJ: Prentice Hall, 1982.
283. Gonzalez, R. C. and Woods, R. E., Digital Image Processing, New York: Addison-Wesley, 2002.
284. Gosh, P. K., “A mathematical model for shape description using Minkowski operators,” Compt. Vision, Graphics, and Image Processing, vol. 44, no. 3, pp. 239–269, Dec. 1988.
285. Haralick, R. M., Sternberg, S. K., and Zhuang, X., “Image analysis using mathematical morphology,” IEEE Trans. Pattern Analysis and Machine Intelligence, vol. 9, no. 4, pp. 532–550, July 1987.
286. Jang, B. K. and Chin, R. T., “Analysis of thinning algorithms using mathematical morphology,” IEEE Trans. Pattern Analysis and Machine Intelligence, vol. 12, no. 6, pp. 541–551, June 1990.
287. Kaul, A., Computing Minkowski Sums, Ph.D. thesis, Department of Mechanical Engineering, Columbia University, 1993.
288. Korein, J., A Geometric Investigating Reach, MA: MIT Press, 1985.
289. Leu, M. C., Park, S. H., and Wang, K. K., “Geometric representation of translational swept volumes and its applications,” ASME Journal of Engineering for Industry, vol. 108, no. 2, pp. 113–119, 1986.
290. Martelli, A., “An application of heuristic search methods to edge and contour detection,” Communication ACM, vol. 19, no. 2, pp. 73–83, Feb. 1976.
291. Martin, R. R. and Stephenson, P. C., “Sweeping of three dimensional objects,” Computer Aided Design, vol. 22, no. 4, pp. 223–234, May 1990.
292. Morales, A. and Acharya, R., “Statistical analysis of morphological openings,” IEEE Trans. Signal Processing, vol. 41, no. 10, pp. 3052–3056, Oct. 1993.
293. Mott-Smith, J. C. and Baer, T., “Area and volume coding of pictures,” in Picture Bandwidth Compression, edited by T. S. Huang and O. J. Tretiak, New York: Gordon and Beach, 1972.
294. Pennington, A., Bloor, M. S., and Balila, M., “Geometric modeling: A contribution toward intelligent robots,” Proc. 13th Inter. Symposium on Industrial Robots, pp. 35–54, 1983.
295. Ragothama, S. and Shapiro, V., “Boundary representation deformation in parametric solid modeling,” ACM Transactions on Graphics, vol. 17, no. 4, pp. 259–286, Oct. 1998.
296. Requicha, A. A. G., “Representations for rigid solids: Theory, methods, and systems,” ACM Computing Surveys, vol. 12, no. 4, pp. 437–464, Dec. 1980.
297. Requicha, A. A. G. and Voelcker, H. B., “Solid modeling: A historical summary and contemporary assessment,” IEEE Computer Graphics and Applications, vol. 2, no. 2, pp. 9–24, Mar. 1982.
298. Roerdink, J. B. T. M., “Group morphology,” Pattern Recognition, vol. 33, no. 6, pp. 877–895, June 2000.
299. Rossignac, J. and Requicha, A. A. G., “Offsetting operations in solid modeling,” Production Automation Project, University of Rochester, NY Tech, Memo 53, 1985.
300. Rossignac, J., “CSG-Brep duality and compression,” Proc. ACM Symposium on Solid Modeling and Applications, Saarbrucken, Germany, pp. 59–66, 2002.
301. Russ, J. C., The Image Processing Handbook, CRC Press, 1992.
302. Serra, J., Image Analysis and Mathematical Morphology, London: Academic Press, 1982.
303. Serra, J., Image Analysis and Mathematical Morphology, New York: Academic Press, vol. 2, 1988.
304. Shih, F. Y., “Object representation and recognition using mathematical morphology model,” Journal of Systems Integration, vol. 1, no. 2, pp. 235–256, Aug. 1991.
305. Shih, F. Y. and Mitchell, O. R., “Threshold decomposition of gray-scale morphology into binary morphology,” IEEE Trans. on Pattern Analysis and machine Intelligence, vol. 11, no. 1, pp. 31–42, Jan. 1989.
306. Shih, F. Y. and Mitchell, O. R., “A mathematical morphology approach to Euclidean distance transformation,” IEEE Trans. on Image Processing, vol. 1, no. 2, pp. 197–204, Apr. 1992.
307. Shih, F. Y. and Cheng, S., “Adaptive mathematical morphology for edge linking,” Information Sciences, vol. 167, no. 1–4, pp. 9–21, Dec. 2004.
308. Shih, F. Y., Gaddipati, V., and Blackmore, D., “Error analysis of surface fitting for swept volumes,” Proc. Japan-USA Symp. Flexible Automation, Kobe, Japan, pp. 733–737, July 1994.
309. Shiroma, Y., Okino, N., and Kakazu, Y., “Research on three-dimensional geometric modeling by sweep primitives,” Proc. of CAD, Brighton, United Kingdom, pp. 671–680, 1982.
310. Shiroma, Y., Kakazu, Y., and Okino, N., “A generalized sweeping method for CSG modeling,” Proc. ACM Symposium on Solid Modeling Foundations and CAD/CAM Applications, Austin, Texas, pp. 149–157, 1991.
311. Stevenson, R. L. and Arce, G. R., “Morphological filters: statistics and further syntactic properties,” IEEE Trans. Circuits and Systems, vol. 34, no. 11, pp. 1292–1305, Nov. 1987.
312. Verly, J. G. and Delanoy, R. L., “Adaptive mathematical morphology for range imagery,” IEEE Trans. Image Process., vol. 2, no. 2, pp. 272–275, Apr. 1993.
313. Voelcker, H. B. and Hunt, W. A., “The role of solid modeling in machining process modeling and NC verification,” SAE Tech. Paper #810195, 1981.
314. Wang, W. P. and Wang, K. K., “Geometric modeling for swept volume of moving solids,” IEEE Computer Graphics and Applications, vol. 6, no. 12, pp. 8–17, Dec. 1986.
315. Brooks, R. A., “Solving the find-path problem by good representation of free space,” IEEE Trans. Systems, Man, and Cybernetics, vol. 13, no. 3, pp. 190–197, Mar./Apr. 1983.
316. Ghosh, P. K., “A solution of polygon containment, spatial planning, and other related problems using Minkowski operations,” Comput. Vision, Graphics, Image Processing, vol. 49, no. 1, pp.1–35, 1990.
317. Hwang, Y. K. and Ahuja, N., “Gross motion planning—a survey,” ACM Computing Surveys, vol. 24, no. 3, pp. 219–290, 1992.
318. Kambhampati, S. K. and Davis, L. S., “Multiresolution path planning for mobile robots,” IEEE Trans. Robotics and Automation, vol. 2, no. 3, pp. 135–145, Sep. 1994.
319. Latombe, J., Robot Motion Planning, Kluwer Academic Publishers, Boston, MA, 1991.
320. Lin, P. L. and Chang, S., “A shortest path algorithm for a nonrotating object among obstacles of arbitrary shapes,” IEEE Trans. Systems, Man, and Cybernetics, vol. 23, no. 3, pp. 825–833, 1993.
321. Lozano-Perez, T., “A simple motion planning algorithm for general robot manipulators,” IEEE Trans. Robotics and Automation, vol. 3, no. 3, pp. 224–238, 1987.
322. Pei, S.-C., Lai, C.-L., and Shih, F. Y., “A morphological approach to shortest path planning for rotating objects,” Pattern Recognition, vol. 31, no. 8, pp. 1127–1138, 1998.
323. Piper, J. and Granum, E., “Computing distance transformation in convex and non-convex domains,” Pattern Recognition, vol. 20, no. 6, pp. 599–615, June 1987.
324. Serra, J., Image Analysis and Mathematical Morphology, New York: Academic, 1982.
325. Shih, F. Y. and Mitchell, O. R., “Threshold decomposition of grayscale morphology into binary morphology,” IEEE Trans. Pattern Analysis and Machine Intelligence, vol. 11, no. 1, pp. 31–42, Jan. 1989.
326. Shih, F. Y., Wu, Y., and Chen, B., “Forward and backward chain-code representation for motion planning of cars,” Pattern Recognition and Artificial Intelligence, vol. 18, no. 8, pp. 1437–1451, Dec. 2004.