2-D shape representation and recognition by lattice computing techniques

Authors:
V. G. Kaburlasos;A. Amanatiadis;S. E. Papadakis
Affiliations:
Department of Industrial Informatics, Technological Educational Institution of Kavala, Kavala, Greece;Department of Industrial Informatics, Technological Educational Institution of Kavala, Kavala, Greece;Department of Industrial Informatics, Technological Educational Institution of Kavala, Kavala, Greece
Venue:
HAIS'10 Proceedings of the 5th international conference on Hybrid Artificial Intelligence Systems - Volume Part II
Year:
2010

Citing 3
Cited 0

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Granular fuzzy inference system (FIS) design by lattice computing

HAIS'10 Proceedings of the 5th international conference on Hybrid Artificial Intelligence Systems - Volume Part II

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Abstract

We consider binary images such that an image includes a single 2-D shape, from which we extract three populations of three different (shape) descriptors, respectively Each population is represented by an Intervals' Number, or IN for short, in the mathematical lattice (F,≼) of INs In conclusion, a 2-D shape is represented in the Cartesian product lattice (F3,≼) We present a 2-D shape classification scheme based on fuzzy lattice reasoning (FLR) Preliminary experimental results have been encouraging We discuss the potential of Lattice Computing (LC) techniques in image representation and recognition applications.