Abstract
There is a wish to be able to enter Chinese text into mobile computing devices in real-time at the speed of speech. Handwritten shorthand schemes offer the potential to achieve this data recording rate. A new overall solution to the segmentation and classification of phonetic features in Renqun shorthand, which records Chinese characters phonetically, is proposed in this paper. A new writing rule is introduced to improve the machine readability of Renqun shorthand. Evaluation results show that the introduction of the new rule has a positive effect on the recognition performance. The recognition accuracies for vocalized outlines and shortforms following the new rule achieve 83% and 84.07%, respectively.
| Original language | English |
|---|---|
| Pages (from-to) | 873-883 |
| Journal | Pattern Recognition Letters |
| Volume | 28 |
| Issue number | 7 |
| DOIs | |
| Publication status | Published - 2007 |
Keywords
- Computer Vision
- Image Processing
- Pattern Recognition and Data Mining
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