on-line handwritten chinese character recognition based on inter-radical stochastic context-free grammar
文献类型：会议论文
| 作者 | Ma Long-Long ; Wu Jian |
| 出版日期 | 2012 |
| 会议名称 | 2012 Annual International Joint Conference on Neural Networks, IJCNN 2012, Part of the 2012 IEEE World Congress on Computational Intelligence, WCCI 2012 |
| 会议日期 | June 10, 2012 - June 15, 2012 |
| 会议地点 | Brisbane, QLD, Australia |
| 关键词 | Context free grammars Dynamic positioning Forestry Neural networks Trees (mathematics) |
| 页码 | - |
| 中文摘要 | This paper presents a new radical-based recognition method for online handwritten Chinese characters focusing on their hierarchical structure. Inter-radical stochastic context-free grammar (SCFG) is introduced to represent the character generation process where radicals as structure elements. Inter-radical SCFG combines the radical shape likelihood with the relative position likelihood between radicals/meta-radicals. The character pattern is over-segmented by three-layer nested pre-segmentation. Character-radical dictionaries of all character classes are unified into several big tree structures where character-parts (sub-structures) are shared by different character classes. Combining inter-radical SCFG with tree structural character-radical dictionaries, the optimal radical segmentation and recognition result is obtained during hierarchical dynamic programming (DP) search. We have implemented the method to Chinese characters of left-right and up-down structures. Experimental results on a sample set of 5,773 character classes consisting of 1,149 radicals show the proposed method is comparable to our previous method. © 2012 IEEE. |
| 英文摘要 | This paper presents a new radical-based recognition method for online handwritten Chinese characters focusing on their hierarchical structure. Inter-radical stochastic context-free grammar (SCFG) is introduced to represent the character generation process where radicals as structure elements. Inter-radical SCFG combines the radical shape likelihood with the relative position likelihood between radicals/meta-radicals. The character pattern is over-segmented by three-layer nested pre-segmentation. Character-radical dictionaries of all character classes are unified into several big tree structures where character-parts (sub-structures) are shared by different character classes. Combining inter-radical SCFG with tree structural character-radical dictionaries, the optimal radical segmentation and recognition result is obtained during hierarchical dynamic programming (DP) search. We have implemented the method to Chinese characters of left-right and up-down structures. Experimental results on a sample set of 5,773 character classes consisting of 1,149 radicals show the proposed method is comparable to our previous method. © 2012 IEEE. |
| 收录类别 | EI |
| 会议主办者 | IEEE Computational Intelligence Society (CIS); International Neural Network Society (INNS) |
| 会议录 | Proceedings of the International Joint Conference on Neural Networks
 |
| 语种 | 英语 |
| ISBN号 | 9781467314909 |
| 源URL | [http://ir.iscas.ac.cn/handle/311060/15765]  |
| 专题 | 软件研究所_软件所图书馆_会议论文 |
| 推荐引用方式 GB/T 7714 | Ma Long-Long,Wu Jian. on-line handwritten chinese character recognition based on inter-radical stochastic context-free grammar[C]. 见:2012 Annual International Joint Conference on Neural Networks, IJCNN 2012, Part of the 2012 IEEE World Congress on Computational Intelligence, WCCI 2012. Brisbane, QLD, Australia. June 10, 2012 - June 15, 2012. |
入库方式： OAI收割
来源：软件研究所
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