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Utilizing Structural Context for Region Classification

  • Zhiyong Wang
  • David D. Feng
Conference paper
Part of the IFIP International Federation for Information Processing book series (IFIPAICT, volume 228)

Abstract

In this paper, we propose to take structural context of image regions into account for region classification through a structural neural network. Firstly, a tree structure of each region is formed to characterize the relationship among the region and its neighbours. Such structures integrate both visual attributes of regions and their structural contexts. Then the structural representations are learned through a Back-propagation Through Structure (BPTS) training algorithm. Comprehensive experimental results demonstrate that our proposed approach has a great potential in region classification.

Keywords

Region Classification Structural Context Neural Networks 

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Copyright information

© International Federation for Information Processing 2006

Authors and Affiliations

  • Zhiyong Wang
    • 1
  • David D. Feng
    • 1
    • 2
  1. 1.School of Information TechnologiesThe University of SydneyAustralia
  2. 2.Department of Electronic and Information EngineeringHong Kong Polytechnic UniversityHong Kong

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