In this paper a novel 2D shape recognition approach is proposed. The main idea is to exploit in this context the huge amount of work carried out by bioinformaticians in the biological sequence analysis research field. In the proposed approach, we encode shapes as biological sequences, employing standard and well established sequence alignment tools to devise a similarity score, finally used in a nearest neighbour scenario. Despite its simplicity, obtained results on standard datasets are really encouraging.
2D shape recognition using biological sequence alignment tools
BICEGO, Manuele;LOVATO, PIETRO
2012-01-01
Abstract
In this paper a novel 2D shape recognition approach is proposed. The main idea is to exploit in this context the huge amount of work carried out by bioinformaticians in the biological sequence analysis research field. In the proposed approach, we encode shapes as biological sequences, employing standard and well established sequence alignment tools to devise a similarity score, finally used in a nearest neighbour scenario. Despite its simplicity, obtained results on standard datasets are really encouraging.
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