This paper presents a novel 2D shape classification 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 Springer-Verlag Berlin Heidelberg.
CITATION STYLE
Lovato, P., & Bicego, M. (2012). 2D shapes classification using blast. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 7626 LNCS, pp. 273–281). https://doi.org/10.1007/978-3-642-34166-3_30
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