Rotation-Invariant Pattern Recognition: A Procedure Slightly Inspired on Olfactory System and Based on Kohonen Network

  • M. B. Palermo
  • L. H. A. Monteiro
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4132)


A computational scheme for rotation-invariant pattern recognition based on Kohonen neural network is developed. This scheme is slightly inspired on the vertebrate olfactory system, and its goal is to recognize spatiotemporal patterns produced in a two-dimensional cellular automaton that would represent the olfactory bulb activity when submitted to odor stimuli. The recognition occurs through a multi-layer Kohonen network that would represent the olfactory cortex. The recognition is invariant to rotations of the patterns, even when a noise lower than 1% is added.


Olfactory Bulb Cellular Automaton Spatiotemporal Pattern Olfactory System Output Matrix 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer-Verlag Berlin Heidelberg 2006

Authors and Affiliations

  • M. B. Palermo
    • 1
  • L. H. A. Monteiro
    • 1
    • 2
  1. 1.Universidade Presbiteriana Mackenzie, Pós-graduação em Engenharia Elétrica, Escola de EngenhariaSão PauloBrazil
  2. 2.Departamento de Engenharia de Telecomunicações e Controle, Escola PolitécnicaUniversidade de São PauloSão PauloBrazil

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