Chapter

Fuzzy Logic and Applications

Volume 2955 of the series Lecture Notes in Computer Science pp 216-223

Out-of-Core Segmentation by Deformable Models

  • Gilson GiraldiAffiliated withNational Laboratory for Scientific Computing, LNCC
  • , Leandro SchaeferAffiliated withNational Laboratory for Scientific Computing, LNCC
  • , Ricardo FariasAffiliated withNational Laboratory for Scientific Computing, LNCC
  • , Rodrigo SilvaAffiliated withNational Laboratory for Scientific Computing, LNCC

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Abstract

Memory limitations can lower the performance of segmentation applications for large images or even make it undoable. In this paper we address this problem through out-of-core techniques. Specifically, we integrate the T-Surfaces model, and out-of-core isosurface generation methods in a general framework for segmentation of large image volumes. T-Surfaces is a parametric deformable model based on a triangulation of the image domain, a discrete surface model and an image threshold. Isosurface generation techniques have been implemented through an out-of-core method that uses a k-d-tree-like structures, called meta-cell technique. By using the meta-cell framework, we present an out-of-core version of a segmentation method based on T-Surfaces and isosurface extraction. We demonstrate our out-of-core methodology (Meta-Cell, Isosurfaces, T-Surfaces) for segmentation of grey level images.