Type-2 Fuzzy Markov Random Fields to Handwritten Character Recognition

Authors:
Jia Zeng;Zhi-Qiang Liu
Affiliations:
City University of Hong Kong, P.R.CHINA;City University of Hong Kong, P.R.CHINA
Venue:
ICPR '06 Proceedings of the 18th International Conference on Pattern Recognition - Volume 01
Year:
2006

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Cited 1

Interval type-2 fuzzy markov chains: type reduction

ICIC'11 Proceedings of the 7th international conference on Advanced Intelligent Computing Theories and Applications: with aspects of artificial intelligence

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Abstract

This paper integratesMarkov random fields (MRFs) with type-2 fuzzy sets (T2 FSs) referred to as T2 FMRFs, which can handle the fuzziness of the labeling space as well as the randomness of observations within the unified framework. Because fuzzy and random uncertainties exist in many computer vision problems, we extend the maximum a posteriori (MAP) criterion for the best labeling configuration by T2 FSs operations. We apply T2 FMRFs as character models to similar handwritten Chinese character recognition on ETL- 9B and KAIST databases. Experimental results show that T2 FMRFs have a better classification and generalization ability for similar patterns than classical MRFs.