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Review of pattern matching approaches

Published online by Cambridge University Press:  07 July 2009

D. Manfaat ,
A. H. B. Duffy  and
B. S. Lee
D. Manfaat
Affiliation:
CAD Centre Department of Ship and Marine Technology, University of Strathclyde, Glasgow GI lXJ, Scotland
A. H. B. Duffy
Affiliation:
CAD Centre
B. S. Lee
Affiliation:
Department of Ship and Marine Technology, University of Strathclyde, Glasgow GI lXJ, Scotland
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Abstract

This paper presents a review of pattern matching techniques. The application areas for pattern matching are extensive, ranging from CAD systems to chemical analysis and from manufacturing to image processing. Published techniques and methods are classified and assessed within the context of three key issues: pattern classes, similarity types and matching methods. It has been shown that the techniques and approaches are as diverse and varied as the applications.

Type
Research Article
Information
The Knowledge Engineering Review , Volume 11 , Issue 2 , June 1996 , pp. 161 - 189
Copyright
Copyright © Cambridge University Press 1996

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References

Akutsu, T, 1992. “Algorithms for determining the geometrical congruity in two and three dimensions” In: Inagaki, Y, Iwama, K, Nishizeki, T, Ibaraki, T and Yamashita, M (eds) 1992. Algorithms and Computation 279–288. Springer-Verlag.Google Scholar
Akutsu, T, 1995. “Efficient and robust three dimensional pattern matching algorithms using hashing and dynamic programming techniques” In: Proceedings of the Hawaii International Conference on System Sciences 5 225–234. IEEE.Google Scholar
Akutsu, T, Suzuki, E and Ohsuga, S 1991. “Logic-based approach to expert systems in chemistry” Knowledge-Based Systems 4 (2) 103–116.CrossRefGoogle Scholar
Alvisi, L and Odorico, R, 1988. “A rule based approach for pattern recognition in planar geometric figures” Computer Physics Communications 51(3) 443–450.CrossRefGoogle Scholar
Ballard, DH and Brown, CM, 1982. Computer Vision Prentice-Hall.Google Scholar
Bareiss, R (ed) 1991. Proceedings: Case-Based Reasoning Workshop 1991 Morgan Kaufmann.Google Scholar
Barr, A and Feigenbaum, EA (eds) 1982. The Handbook of Artificial Intelligence vol 2 Pitman.Google Scholar
Barsalou, LW, 1989. “Intraconcept similarity and its implications for interconcept similarity” In: Vosniadou, S and Ortony, A (eds) Similarity and Analogical Reasoning Chapter 3, 76–121. Cambridge University Press.Google Scholar
Berge, C, 1976. Graphs and Hypergraphs Elsevier.Google Scholar
Clark, A, 1989. Microcognitron: Philosophy, Cognitive Science and Parallel Distributed Processing MIT Press.Google Scholar
Cohen, PR and Feigenbaum, EA (eds) 1982. The Handbook of Artificial Intelligence 3. Pitman.Google Scholar
Cooper, MC, 1989. “Formal hierarchical object models for fast template matching” The Computer J 32 (4) 351–361.CrossRefGoogle Scholar
Coyne, RD and Newton, S, 1989. “A tutorial on neural networks and expert systems for design” In: Gero, JS and Sudweeks, F (eds) Expert Systems in Engineering, Architecture & Construction 321–337. Sydney.Google Scholar
Coyne, RD, Newton, S and Sudweeks, F. 1989. “Modelling the emergence of schemas in design reasoning” In: Modelling Creativity and Knowledge Based Creative Design 173–205. Design Computing Unit, Department of Architectural and Design Science, University of Sydney.Google Scholar
Coyne, RD and Postmus, AG, 1990. “Spatial applications of neural networks in computer-aided design” Artificial Intelligence in Engineering 5 (1) 9–22.Google Scholar
Date, Cj, 1990. An Introduction to Database Systems (5th ed) Addison-Wesley.Google Scholar
Dave, B, Schmitt, G, Faltings, B and Smith, L, 1994. “Case based designs in architecture” In: Gero, JS and Sudweeks, F (eds) Artificial Intelligence in Design 94 145–162. Kluwer.Google Scholar
Domeshek, E and Kolodner, J, 1991. “Toward a case-based aid for conceptual design” Internationali Expert Systems 4 (2) 201–220.Google Scholar
Domeshek, E and Kolodner, J, 1992. ” In: Gero, JS (ed) Artificial Intelligence in Design' 92 497–516. Kluwer.Google Scholar
Duffy, AHB, 1989. Expert Systems in Engineering Course Notes, CAD Centre, University of Strathclyde, Glasgow, Scotland.Google Scholar
Duffy, AHB and Kerr, SM, 1993. “Customised perspectives of past designs from automated group rationalitations” Artificial Intelligence in Engineering 8(3) 182–200.CrossRefGoogle Scholar
Fodor, J, 1968. “The appeal to tacit knowledge in psychological explanation” J Philosophy 65 627–640.CrossRefGoogle Scholar
Fu, KS (ed) 1976. Digital Pattern Recognition In Communication and cybernetics Springer-Verlag.CrossRefGoogle Scholar
Fukushima, K, 1988. “Neocognitron: a hierarchical neural network capable of visual pattern recognition” Neural Networks 1 119–130.CrossRefGoogle Scholar
Fukushima, K and Miyake, S, 1982. “Neocognitron: a new algorithm for pattern recognition tolerant of deformations and shifts in position” Pattern Recognition 15 (6) 455–469.CrossRefGoogle Scholar
Gellert, W, Gottwald, S, Hellwich, M, Kastner, H and Kustner, H, 1989. The VNR Concise Encyclopedia of Mathematics (2nd ed) Van Nostrand Reinhold.Google Scholar
Giretti, A, Spalazzi, L and Lemma, M, 1994. “A.S.A: an interactive approach to architectural design” In: Gero, JS and Sudweeks, F (eds) Artificial Intelligence in Design '94 93–108. Kluwer.Google Scholar
Gross, M, Zimring, C and Do, E, 1994. “Using diagrams to access a case base of architectural designs” In: Gero, JS and Sudweeks, F (eds) Artificial Intelligence in Design '94 129–144. Kluwer.Google Scholar
Hall, G and Matias, A, 1993. “Rotation, scale and translation invariant template matching on a transputer network” Microprocessors and Microsystems 17 (6) 333–340.CrossRefGoogle Scholar
Harary, F, 1969. Graph Theory Addison-Wesley.CrossRefGoogle Scholar
Hopcroft, JE and Tarjan, RE, 1973. “AV log V algorithm for isomorphism of tri-connected planar graphs” J Computer and System Sciences 7 323–331.Google Scholar
Jackson, P, 1986. Introduction to Expert Systems Addison-Wesley.Google Scholar
Kabsch, W, 1976. “A solution for the best rotation to relate two sets of vectors” Acta Crystallography A 32 922–923.CrossRefGoogle Scholar
Kalvin, A.Schonberg, E, Schwartz, JT and Sharir, M, 1986. “Two-dimensional, model-based, boundary matching using footprints” International Journal of Robotics Research 5 (4) 38–55.CrossRefGoogle Scholar
Karbacher, S, 1990. “Associative object recognition by hierarchic template matching” Optical Engineering 29(12) 1449–1457.Google Scholar
Kolodne, JL, 1993. Case-Based Reasoning Morgan Kaufmann.CrossRefGoogle Scholar
Korn, GA, 1990. “Interactive statistical experiments with template-matching neural networks” IEEE Trans Systems, Man, and cybernetics 20 (5) 1146–1152, September/October.Google Scholar
Maher, ML and Zhao, F, 1987. “Using experience to plan the synthesis of new designs” In: Gero, JS (ed) Expert Systems in Computer-Aided Design 349–373. Elsevier.Google Scholar
McClelland, JL and Rumelhart, DE, 1987. Parallel Distributed Processing: Explorations in the Microstructure of Cognition: 2: Psychological and Biological Models MIT Press.Google Scholar
McGregor, JJ, 1982. “Backtrack search algorithms and maximal common subgraph problem” Software- Practice and Experience 12 23–34.CrossRefGoogle Scholar
McLarcn, N, 1994. “A sonar-based navigation system for underwater vehicles” PhD thesis, Department of Ship and Marine Technology, University of Strathclyde Glasgow, Scotland.Google Scholar
Mecran, S, Pratt, MJ and Key, I M, 1993. “The use of PROLOG in the automatic recognition of manufacturing features from 2-D drawings” Engineering Applications of Artificial Intelligence 6 (5) 409–423.Google Scholar
Peschl, MF, 1990. “Neural networks and symbolic computation in cognitive modelling” In: Gardin, F and Mauri, G (eds) Computational Intelligence, 11 29–235. Elsevier.Google Scholar
Peters, TJ, 1992, “Encoding mechanical design features for recognition via neural nets” Research in Engineering Design 4 67–74.Google Scholar
Preparata, FP and Shamos, MI, 1985. Computational Geometry, An Introduction Texts and Monographs in Computer Science. Springer-Verlag.Google Scholar
Putnam, H, 1960. “Minds and machines” In: Hook, S (ed) Dimensions of Mind New York University Press.Google Scholar
Reihani, K, 1994. “Processing hierarchy for 2-D image structures” Computing Systems in Engineering 5 (1) 41–54.CrossRefGoogle Scholar
Rips, LJ, 1989. “Similarity, typicality, and categorization” In:Vosniadou, S and Ortony, A (eds) Similarity and Analogical Reasoning Chapter 1, 21–59. Cambridge University Press.Google Scholar
Rooncy, J and Steadman, P (eds) 1987. Principles of Computer-aided Design Pitman/Open University.Google Scholar
Rumclhart, DE, 1989. “Toward a microstructural account of human reasoning” In: Vosniadou, S and Ortony, A (eds) Similarity and Analogical Reasoning Chapter 10, 298–312. Cambridge: Cambridge University Press.Google Scholar
Schneider, R, Kriegel, H-P, Seeger, B and Heep, S, 1989. “Geometry-based similarity retrieval of rotational parts” Data and Knowledge Systems for Manufacturing and Engineering 150–160, 10.Google Scholar
Schwartz, JT and Sharir, M, 1987. “Identification of partially obscured objects in two and three dimensions by matching noisy characteristic curves” International Journal of Robotic Research 6 (2) 29–44.Google Scholar
Smith, LB, 1989. “From global similarities to kinds of similarities: the construction of dimensions in development” In: Vosniadou, S and Ortony, A (eds) Similarity and Analogical Reasoning Chapter 5. 146–178. Cambridge University Press.CrossRefGoogle Scholar
Smith, EE and Osherson, DN, 1989. “Similarity and decision making” In: Vosniadou, S and Ortony, A (eds) Similarity and Analogical Reasoning Chapter 2, 60–75. Cambridge University Press.CrossRefGoogle Scholar
Sussenguth, EH Jr, 1965. “A graph-theoretic algorithm for matching chemical structures” J Chemical Documentation 5 35–43.Google Scholar
Teo, MY and Sim, SK, 1995. “Training the neocognitron network using design of experiments” Artificial Intelligence in Engineering 9 (2) 85–94.CrossRefGoogle Scholar
Vosniadou, S and Ortony, A, 1989. Similarity and Analogical Reasoning Cambridge University Press.Google Scholar
Voβ, A, Coulon, C-H, Grather, W, Linowski, B, Schaaf, J, Bartsch-Sporl, B, Borner, K, Tammer, EC, Durschke, H and Knauff, M, 1994. “Retrieval of similar layouts—about a very hybrid approach in FABEL” In: Gero, JS and Sudweeks, F(eds) Artificial Intelligence in Design '94 625–640. Kluwer.Google Scholar
Waterman, DA, 1986. A Guide to Expert Systems Addison-Wesley.Google Scholar