Similitude-invariant pattern recognition using parallel distributed processing

  • Authors:
  • K. Prazdny

  • Affiliations:
  • Artificial Intelligence Center, FMC Corporation, Santa Clara, CA

  • Venue:
  • AAAI'87 Proceedings of the sixth National conference on Artificial intelligence - Volume 2
  • Year:
  • 1987

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Abstract

Translation-, rotation-, and scale-invariant recognition of multiple, superimposed, partially specified or occluded objects can be accomplished in a fast, simple, distributed and parallel fashion using localizable features with intrinsic orientation. All known objects are recognized, localized, and segmented simultaneously. The method is robust and efficient.