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. © Springer-Verlag Berlin Heidelberg 2003.
CITATION STYLE
Hanmandlu, M., Yusof, M. H. M., & Madasu, V. K. (2003). Fuzzy modeling based recognition of multi-font numerals. Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 2781, 204–211. https://doi.org/10.1007/978-3-540-45243-0_27
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