Rotation-Invariant pattern recognition: a procedure slightly inspired on olfactory system and based on kohonen network

Authors:
M. B. Palermo;L. H. A. Monteiro
Affiliations:
Universidade Presbiteriana Mackenzie, Pós-graduação em Engenharia Elétrica, Escola de Engenharia, São Paulo, SP, Brazil;Universidade Presbiteriana Mackenzie, Pós-graduação em Engenharia Elétrica, Escola de Engenharia, São Paulo, SP, Brazil
Venue:
ICANN'06 Proceedings of the 16th international conference on Artificial Neural Networks - Volume Part II
Year:
2006

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Abstract

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.