Abstract
2D shape recognition from a set of points is largely used in several imaging areas such as geometric modeling, image visualization or medical image analysis. However, the perceived shape of a set of points is subjective. It is mainly influenced by the spatial arrangement of the points and by several cognitive factors. The Delaunay filtration methods derived from the well-known α-shapes, like LDA-α-shapes or conformal-α-shapes, provide a family of shapes capturing the intuitive notion of “crude” versus “fine” shape of a set of points. In this paper, a quantitative criterion based on shape measurements is defined for extracting the “optimal” shape from this family that best corresponds to the human visual perception. A novel automatic shape recognition method is proposed and successfully evaluated on the KIMIA image database, where the reference shapes are known and sampled by generating 2D point sets.
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© 2011 Springer-Verlag Berlin Heidelberg
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Presles, B., Debayle, J., Maillot, Y., Pinoli, JC. (2011). Automatic Recognition of 2D Shapes from a Set of Points. In: Kamel, M., Campilho, A. (eds) Image Analysis and Recognition. ICIAR 2011. Lecture Notes in Computer Science, vol 6753. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-21593-3_19
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DOI: https://doi.org/10.1007/978-3-642-21593-3_19
Publisher Name: Springer, Berlin, Heidelberg
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