Fuzzy modeling based recognition of multi-font numerals


Hanmandlu, Madasu and Mohd. Hafizuddin Mohd Yusof, and Madasu, Vamsi Krishna (2003) Fuzzy modeling based recognition of multi-font numerals. In: Pattern Recognition. Lecture Notes in Computer Science, 2781 (2781). Springer Berlin Heidelberg, pp. 204-211. ISBN 978-3-540-40861-1

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In this paper, we present a new scheme for off-line recognition of multi-font numerals using the Takagi-Sugeno (TS) model. In this scheme, the binary image of a character is partitioned into a fixed number of sub-images called boxes. The features consist of normalized vector distances (gamma) from each box. Each feature extracted from different fonts gives rise to a fuzzy set. However, when we have a small number of fonts as in the case of multi-font numerals, the choice of a proper fuzzification function is crucial. Hence, we have devised a new fuzzification function involving parameters, which take account of the variations in the fuzzy sets. The new fuzzification function is employed in the TS model for the recognition of multi-font numerals.

Item Type: Book Section
Subjects: Q Science > QA Mathematics > QA71-90 Instruments and machines > QA75.5-76.95 Electronic computers. Computer science
Divisions: Faculty of Computing and Informatics (FCI)
Depositing User: Ms Rosnani Abd Wahab
Date Deposited: 24 Aug 2011 01:43
Last Modified: 23 Dec 2013 04:01
URII: http://shdl.mmu.edu.my/id/eprint/2617


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