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- W2170959797 abstract "The problem of handwritten Chinese character recognition is solved by matching character stroke segments using an iteration scheme. Length and orientation similarity properties, and coordinate overlapping ratios are used to define a measure of similarity between any two stroke segments. The initial measures of similarity between the stroke segments of the input and template characters are used to set up a match network which includes all the match relationships between the input and template stroke segments. Based on the concept of at-most-one to one mapping an iteration scheme is employed to adjust the match relationships, using the contextual information implicitly contained in the match network, so that the match relationships can get into a stable state. From the final match relationships, matched stroke-segment pairs are determined by a mutually-best match strategy and the degree of similarity between the input and each template character is evaluated accordingly. Certain structure information of Chinese characters is also used in the evaluation process. The experimental results show that the proposed approach is effective. For recognition of Chinese characters written by a specific person, the recognition rate is about 96%. If the characters of the first three ranks are checked in counting the recognition rate, the rate rises to 99.6%." @default.
- W2170959797 created "2016-06-24" @default.
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- W2170959797 date "1991-06-01" @default.
- W2170959797 modified "2023-10-12" @default.
- W2170959797 title "RECOGNIZING HANDWRITTEN CHINESE CHARACTERS BY STROKE-SEGMENT MATCHING USING AN ITERATION SCHEME" @default.
- W2170959797 doi "https://doi.org/10.1142/s0218001491000120" @default.
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