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| on-line handwritten chinese character recognition based on inter-radical stochastic context-free grammar | |
| Ma Long-Long; Wu Jian | |
| 2012 | |
| Conference Name | 2012 Annual International Joint Conference on Neural Networks, IJCNN 2012, Part of the 2012 IEEE World Congress on Computational Intelligence, WCCI 2012 |
| Source | Proceedings of the International Joint Conference on Neural Networks |
| Pages | - |
| Conference Date | June 10, 2012 - June 15, 2012 |
| Conference Place | Brisbane, QLD, Australia |
| Indexed Type | EI |
| ISBN | 9781467314909 |
| Department | (1) National Engineering Research Center of Fundamental Software Institute of Software Chinese Academy of Sciences Beijing China |
| English Abstract | 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.; 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. |
| Keyword | Context Free Grammars Dynamic Positioning Forestry Neural Networks Trees (Mathematics) |
| Sponsorship | IEEE Computational Intelligence Society (CIS); International Neural Network Society (INNS) |
| Language | 英语 |
| Content Type | 会议论文 |
| URI | http://ir.iscas.ac.cn/handle/311060/15765 |
| Collection | 中国科学院软件研究所 |
| Recommended Citation GB/T 7714 | Ma Long-Long,Wu Jian. on-line handwritten chinese character recognition based on inter-radical stochastic context-free grammar[C],2012:-. |
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