Convergence of a hill-climbing genetic algorithm for graph matching

Pattern Recognition

Volumn 33, Issue 11, 2000, Pages 1863-1880

  Cross, Andrew D J ^a   Myers, Richard ^a   Hancock, Edwin R ^a  

^a UNIVERSITY OF YORK   (United Kingdom)

Author keywords

[No Author keywords available]

Indexed keywords

GENETIC ALGORITHMS; GRAPH THEORY; POLYNOMIALS;

GRAPH MATCHING; HILL-CLIMBING GENETIC ALGORITHMS;

PATTERN MATCHING;

EID: 0034325435     PISSN: 00313203     EISSN: None     Source Type: Journal    
DOI: 10.1016/S0031-3203(99)00171-5     Document Type: Article

References (32)

1. S. Kirkpatrick C.D. Gelatt M.P. Vecchi Optimisation by simulated annealing Science 220 1983 671 680
2. V. Kumar Algorithms for constraint-satisfaction problems a survey AI Magazine 13 1992 32 44
3. A.K. Mackworth E.C. Freuder The complexity of some polynomial network consistency algorithms for constraint satisfaction problems Artif. Intell. 25 1985 65 74
4. A.K. Mackworth Consistency in a network of relations Aritif. Intell. 8 1977 99 118
5. A. Sanfeliu K.S. Fu A distance measure between attributed relational graphs for pattern recognition IEEE Trans. Systems Man. Cybernet. 13 1983 353 362
6. D. Waltz Understanding line drawings of scenes with shadows P.H. Winton The Psychology of Computer Vision 1975 McGraw-Hill New York
7. L.G. Shapiro R.M. Haralick A metric for comparing relational descriptions IEEE Trans. Pattern Machine Intell. 7 1985 90 94
8. J. Pearl Heuristics Intelligent Search Strategies for Computer Problem Solving 1984 Addison-Wesley Reading, MA
9. ∗ a theoretical comparison of optimisation strategies M. Pelillo E.R. Hancock Energy Minimisation Methods in Computer Vision and Pattern Recognition, Lecture Notes in Computer Science vol. 1223 1997 Springer Berlin 197 212
10. S. Geman D. Geman Stochastic relaxation, Gibbs distributions and Bayesian restoration of images IEEE Trans. Pattern Machine Intell. PAMI-6 1984 721 741
11. B. Gidas A re-normalisation-group approach to image processing problems IEEE Trans. Pattern Machine Intell. 11 1989 164 180
12. A. Yuille Generalised deformable models, statistical physics and matching problems Neural Comput. 2 1990 1 24
13. F. Glover Ejection chains, reference structures and alternating path methods for traveling salesman problems Discrete Appl. Math. 65 1996 223 253
14. E. Rolland H. Pirkul F. Glover Tabu search for graph partitioning Ann. Oper. Res. 63 1996 232 290
15. F. Glover Genetic algorithms and tabu search — hybrids for optimisation Discrete Appl. Math. 49 1995 111 134
16. F. Glover Tabu search for nonlinear and parametric optimisation (with links to genetic algorithms) Discrete Appl. Math. 49 1995 231 255
17. D.B. Fogel An introduction to simulated evolutionary optimisation IEEE Trans. Neural Networks 5 1994 3 14
18. X.F. Qi F. Palmieri Theoretical analysis of evolutionary algorithms with an infinite population in continuous space basic properties of selection and mutation IEEE Trans. Neural Networks 5 1994 102 119
19. X.F. Qi F. Palmieri Theoretical analysis of evolutionary algorithms with an infinite population in continuous space analysis of the diversification role of cross-over IEEE Trans. Neural Networks 5 1994 120 129
20. R. Myers E.R. Hancock Genetic algorithm parameter sets for line labelling Pattern Recognition Lett. 18 1998 1283 1292
21. A.D.J. Cross R.C. Wilson E.R. Hancock Inexact graph matching using genetic search Pattern Recognition 30 1997 953 970
22. E.R. Hancock, J. Kittler, A Bayesian interpretation for the Hopfield network, IEEE International Conference on Neural Networks, 1993, pp. 341–346.
23. E.R. Hancock J. Kittler Discrete relaxation Pattern Recognition 23 1990 711 733
24. E.R. Hancock M. Pelillo A Bayesian interpretation for the exponential correlation associative memory Pattern Recognition Lett. 19 1998 139 149
25. R.C. Wilson, E.R. Hancock, Gauging consistency and controlling structural errors, IEEE Computer Society Computer Vision and Pattern Recognition Conference, 1996.
26. R.C. Wilson E.R. Hancock Structural matching by discrete relaxation IEEE Trans. Pattern Machine Intell. 19 1997 634 648
27. R.C. Wilson E.R. Hancock Structural matching with active triangulations Computer Vision Image Understanding 72 1998 21 38
28. R.C. Wilson, E.R. Hancock, Relational matching with dynamic graph structures, Proceedings of the Fifth International Conference on Computer Vision, 1995, pp. 450–456.
29. H.G. Barrow, R.J. Popplestone, Relational descriptions in picture processing, Machine Intell. 6 (1971).
30. B.T. Messmer, H. Bunke, Efficient error-tolerant subgraph isomomrphism detection, In: D. Dori, A. Bruckstein (Eds.), Shape, Structure and Pattern Recognition, 1995, pp. 231–240.
31. A.K.C. Wong M. You Entropy and distance of random graphs with application to structural pattern recognition IEEE Trans. Pattern Machine Intell. 7 1985 599 609
32. D. Goldberg Genetic Algorithms in search, Optimisation and Learning 1989 Addison-Wesley Reading, MA