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Hierarchical image segmentation using a correspondence with a tree model

Authors
Journal
Pattern Recognition
0031-3203
Publisher
Elsevier
Publication Date
Volume
37
Issue
1
Identifiers
DOI: 10.1016/j.patcog.2003.07.009
Keywords
  • Computer Vision
  • Image Segmentation
  • Hierarchical Analysis
  • Mathematical Morphology
  • Watershed
  • Tree Representation
  • Medical Imaging
Disciplines
  • Computer Science

Abstract

Abstract A new general image segmentation system is presented, based on the calculation of a tree representation of the original image in which image regions are assigned to tree nodes, followed by a correspondence process with a model tree, which embeds the a priori knowledge about the images. For this correspondence, an original algorithm is proposed, which performs the minimization of an error function that quantifies the difference between the input image tree and the model tree. We also present a new algorithm for automatically calculating the model tree from a set of manually segmented images. Results on synthetic and MR brain images are presented.

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