Abstract
This paper describes a novel framework for performing relational graph matching using genetic search. The fitness measure is Bayesian in origin. It gauges relational consistency at both the symbolic and attribute levels. The basic measure of symbolic consistency is Hamming distance, while attribute consistency is measured using Mahalanobis distance. We provide examples of the performance on synthetic graphs containing significant levels of clutter. We also demonstrate that the technique is capable of resolving multiple graphs with significant overlap. The performance advantages over deterministic hill climbing are also demonstrated.
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© 1996 Springer-Verlag Berlin Heidelberg
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Cross, A.D.J., Hancock, E.R. (1996). Inexact graph matching with genetic search. In: Perner, P., Wang, P., Rosenfeld, A. (eds) Advances in Structural and Syntactical Pattern Recognition. SSPR 1996. Lecture Notes in Computer Science, vol 1121. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-61577-6_16
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DOI: https://doi.org/10.1007/3-540-61577-6_16
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