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An unsupervised region growing method for 3D image segmentation

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Computer Analysis of Images and Patterns (CAIP 1995)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 970))

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Abstract

The paper deals with 3D shape decomposition problem, objects are modelled as finite unions of almost-convex primitives. A new region growing method is proposed to extract meaningful objects parts. Parts are individuated by performing a set-partitioning of surface dominating points. The partition step returns labelled seeds from which to start a region growing procedure that propagate labels onto object surface patches. A fuzzy concept of λ-convexity is introduced to test noised real images. Experimental results are given.

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Author information

Authors and Affiliations

  1. Dipartimento di Matematica ed Applicazioni, University of Palermo, Italy

    Franco Chiavetta & Vito Di Gesù

  2. ITI-Vittorio Emanuele III, Palermo, Italy

    Franco Chiavetta

Authors
  1. Franco Chiavetta
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  2. Vito Di Gesù
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Editor information

Václav Hlaváč Radim Šára

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© 1995 Springer-Verlag Berlin Heidelberg

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Chiavetta, F., Di Gesù, V. (1995). An unsupervised region growing method for 3D image segmentation. In: Hlaváč, V., Šára, R. (eds) Computer Analysis of Images and Patterns. CAIP 1995. Lecture Notes in Computer Science, vol 970. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-60268-2_279

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  • DOI: https://doi.org/10.1007/3-540-60268-2_279

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-60268-2

  • Online ISBN: 978-3-540-44781-8

  • eBook Packages: Springer Book Archive

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