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題 名 | Ring Data for Invariant Recognition of Handwritten Chinese Characters |
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作 者 | 曾定章; 邱宏彬; 鄭仁傑; | 書刊名 | Journal of Information Science and Engineering |
卷 期 | 14:2 1998.06[民87.06] |
頁 次 | 頁479-497 |
分類號 | 312.74 |
關鍵詞 | Handwritten Chinese character recognition; Invariant; Ring data; Preclassification; |
語 文 | 英文(English) |
英文摘要 | Few researches have focused on translation-, scale-, and rotation-invariant recognition of handwritten Chinese characters since writing variation is large and invariant features are hard to find. In this study, an adequate normalization process is first used to normalize characters such that they are invariant to translation and scale; then five rotation-invariant features are extracted for invariant recognition. We propose a feature-extraction approach which especially considers the skeleton-distortion problem to effectively extract the desired invariant features. The first four invariant features are used for preclassification to reduce the matching time. The last feature, ring data, is used to construct ring-data vectors and weighted ring-data matrices to individually characterize character samples and characters for invariant recognition. A character set was constructed from 200 handwritten Chinese characters with several different samples of each character in arbitrary orientation. Several experiments were conducted using the caharacter set to evaluate the performance of the proposed preclassification and ring-data matching algorithms. The experimental results show that the proposed approaches work well for invariant handwritten Chinese character recognition and are superior to the moment-invariant matching approach. |
本系統中英文摘要資訊取自各篇刊載內容。