The angular integral of the radon transform (aniRT) as a feature vector in categorization of visual objects

  • Authors:
  • Andrew P. Papliński

  • Affiliations:
  • Monash University, Australia

  • Venue:
  • ISNN'13 Proceedings of the 10th international conference on Advances in Neural Networks - Volume Part I
  • Year:
  • 2013

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Abstract

The recently introduced angular integral of the Radon transform (aniRT) seems to be a good candidate as a feature vector used in categorization of visual objects in a rotation invariant fashion. We investigate application of aniRT in situations when the number of objects is significant, for example, Chinese characters. Typically, the aniRT feature vector spans the diagonal of the visual object. We show that a subset of the full aniRT vector delivers a good categorization results in a timely manner.