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Conference Papers Year : 2005

Reactive tabu search for measuring graph similarity


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 [Champin & Solnon 03]. This generic similarity measure is based on a non-bijective graph matching (like [Boeres & al. 04] and [Ambauen & al. 03]) 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.
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hal-01541534 , version 1 (24-03-2020)



Sébastien Sorlin, Christine Solnon. Reactive tabu search for measuring graph similarity. 5th IAPR-TC-15 workshop on Graph-based Representations in Pattern Recognition, Apr 2005, Poitiers, France. pp.172-182, ⟨10.1007/978-3-540-31988-7_16⟩. ⟨hal-01541534⟩
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