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Fuzzy Modeling Based Recognition of Multi-font Numerals

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Pattern Recognition (DAGM 2003)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 2781))

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Abstract

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 (γ) 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.

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© 2003 Springer-Verlag Berlin Heidelberg

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Hanmandlu, M., Yusof, M.H.M., Madasu, V.K. (2003). Fuzzy Modeling Based Recognition of Multi-font Numerals. In: Michaelis, B., Krell, G. (eds) Pattern Recognition. DAGM 2003. Lecture Notes in Computer Science, vol 2781. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-45243-0_27

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  • DOI: https://doi.org/10.1007/978-3-540-45243-0_27

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-40861-1

  • Online ISBN: 978-3-540-45243-0

  • eBook Packages: Springer Book Archive

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