This paper presents a novel 2D shape classication approach, which exploits in this context the huge amount of work carried out by bioinformaticians in the biological sequence analysis research field. In particular, in the approach presented here, we propose to encode shapes as biological sequences, employing the widely known sequence alignment tool called BLAST (Basic Local Alignment Search Tool) to devise a similarity score, used in a nearest neighbour scenario. Obtained results on standard datasets show the feasibility of the proposed approach.

2D shapes classification using BLAST

LOVATO, PIETRO;BICEGO, Manuele
2012-01-01

Abstract

This paper presents a novel 2D shape classication approach, which exploits in this context the huge amount of work carried out by bioinformaticians in the biological sequence analysis research field. In particular, in the approach presented here, we propose to encode shapes as biological sequences, employing the widely known sequence alignment tool called BLAST (Basic Local Alignment Search Tool) to devise a similarity score, used in a nearest neighbour scenario. Obtained results on standard datasets show the feasibility of the proposed approach.
2012
shape classification; pattern recognition; sequence alignment
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11562/470960
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