A Hierarchical Classifier Using New Support Vector Machine

  • Authors:
  • Yu-Chiang Wang;David Casasent

  • Affiliations:
  • Carnegie Mellon University, Pittsburgh, PA;Carnegie Mellon University, Pittsburgh, PA

  • Venue:
  • ICDAR '05 Proceedings of the Eighth International Conference on Document Analysis and Recognition
  • Year:
  • 2005

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Abstract

A binary hierarchical classifier is proposed to solve the multi-class classification problem. We also require rejection of non-target inputs, which thus producing a very difficult problem. The SVRDM (support vector representation and discrimination machine) classifier is considered at each node in the hierarchy, since it offers good generalization and rejection ability. Using this hierarchical SVRDM classifier with magnitude Fourier transform features, initial recognition and rejection test results on simulated infra-red data are excellent.