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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Guo Rui Jin LianWen |
| Copyright Year | 2007 |
| Description | Author affiliation: South China Univ. of Technol., Guangzhou (Guo Rui; Jin LianWen) |
| Abstract | On-line handwritten Chinese word recognition has recently become an important research topic in the filed of computer vision. However, the segmentation of cursive Chinese word is still an unsolved problem. In this paper, two new features, stroke speed feature and stroke vector feature, are proposed for the segmentation of on-line handwritten Chinese word. Analysis and experiments show that both of the features are easy to implement, with low computation complexity and encouraging correct segmentation accuracy. Furthermore, the stroke vector feature outperforms traditional histogram method and we found it is especially suitable for the segmentation of cursive handwritten word where two characters touch each other or overlap. |
| Starting Page | 1576 |
| Ending Page | 1579 |
| File Size | 207242 |
| Page Count | 4 |
| File Format | |
| ISBN | 9781424415311 |
| DOI | 10.1109/ICAL.2007.4338823 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2007-08-18 |
| Publisher Place | China |
| Access Restriction | Subscribed |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | On-line Chinese character segmentation Histograms Handwriting recognition Computer vision Stroke Vector Feature Automation Asia Stroke Speed Feature Word recognition Character recognition Logistics |
| Content Type | Text |
| Resource Type | Article |
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