Reactive Tabu Search for Measuring Graph Similarity

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Reactive Tabu Search for Measuring Graph Similarity
Abstract. Graph matching is often used for image recognition. Different kinds of graph matchings have been proposed such as (sub)graph isomorphism or error-tolerant graph matching, giving rise to different graph similarity measures. A first goal of this paper is to show that these different measures can be viewed as special cases of a generic similarity measure introduced in [8]. This generic similarity measure is based on a non-bijective graph matching (like [4] and [2]) so that it is well suited to image recognition. In particular, over/under-segmentation problems can be handled by linking one vertex to a set of vertices. In a second part, we address the problem of computing this measure and we describe two algorithms: a greedy algorithm, that quickly computes sub-optimal solutions, and a reactive Tabu search algorithm, that may improve these solutions. Some experimental results are given.
Sébastien Sorlin, Christine Solnon
Added 27 Jun 2010
Updated 27 Jun 2010
Type Conference
Year 2005
Authors Sébastien Sorlin, Christine Solnon
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