Fuzzy modeling based recognition of multi-font numerals
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 e...
| Main Authors: | , , |
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| Other Authors: | |
| Format: | Book Section |
| Language: | English |
| Published: |
Springer Berlin Heidelberg
2003
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| Subjects: | |
| Online Access: | http://shdl.mmu.edu.my/2617/ http://shdl.mmu.edu.my/2617/1/Fuzzy%20modeling%20based%20recognition%20of%20multi-font%20numerals.pdf |
| Summary: | 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. |
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