Threshold of Graph-Based Volumetric Segmentation

  • Dumitru Dan Burdescu
  • Liana Stanescu
  • Marius Brezovan
  • Cosmin Stoica Spahiu
  • Florin Slabu
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 9117)

Abstract

Among the many approaches in performing image segmentation, graph based approach is gaining popularity primarily due to its ability in reflecting global image properties. Volumetric image segmentation can simply result an image partition composed by relevant regions, but the most fundamental challenge in segmentation algorithm is to precisely define the spatial extent of some object, which may be represented by the union of multiple regions. The aim in this paper is to present a new and efficient method as complexity to detect visual objects from color volumetric images and efficient threshold. We present a unified framework for original volumetric segmentation that uses a tree-hexagonal structure defined on the set of the voxels. The advantage of using a tree-hexagonal network superposed over the initial image voxels is that it reduces the execution time and the memory space used, without losing the initial resolution of the image.

Keywords

Volumetric segmentation Graph-based segmentation Dissimilarity Threshold 

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Copyright information

© Springer International Publishing Switzerland 2015

Authors and Affiliations

  • Dumitru Dan Burdescu
    • 1
  • Liana Stanescu
    • 1
  • Marius Brezovan
    • 1
  • Cosmin Stoica Spahiu
    • 1
  • Florin Slabu
    • 2
  1. 1.Computers and Information Technology Department, Faculty of Automatics, Computers and ElectronicsUniversity of CraiovaCraiovaRomania
  2. 2.Departament of Computer ScienceUniversity of CraiovaCraiovaRomania

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