Institutional Repository
| a component-based on-line handwritten tibetan character recognition method using conditional random field | |
| Ma Long-Long; Wu Jian | |
| 2012 | |
| Conference Name | 13th International Conference on Frontiers in Handwriting Recognition, ICFHR 2012 |
| Source | Proceedings - International Workshop on Frontiers in Handwriting Recognition, IWFHR |
| Pages | 704-709 |
| Conference Date | September 18, 2012 - September 20, 2012 |
| Conference Place | Bari, Italy |
| Indexed Type | EI |
| ISSN | 1550-5235 |
| ISBN | 9780769547749 |
| 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 component-based recognition method using conditional random field (CRF) for on-line handwritten Tibetan characters. The character pattern is over-segmented into a sequence of sub-structure blocks. Integrated segmentation and recognition method based on the CRF model is used to determine the component segmentation points from these block sequences. The CRF model combines component shape likelihood with geometrical likelihood. The parameters are learned using an energy minimization method. We build a componentbased spelling rule model to ensure the correct component appearing at a specific structural position. A character-component generation model is presented to reduce component recognition error rate and accelerate the recognition process. Experimental results on MRG-OHTC database show that the proposed method gives promising performance comparing with the holistic method and the component-based conventional path evaluation method. © 2012 IEEE.; This paper presents a new component-based recognition method using conditional random field (CRF) for on-line handwritten Tibetan characters. The character pattern is over-segmented into a sequence of sub-structure blocks. Integrated segmentation and recognition method based on the CRF model is used to determine the component segmentation points from these block sequences. The CRF model combines component shape likelihood with geometrical likelihood. The parameters are learned using an energy minimization method. We build a componentbased spelling rule model to ensure the correct component appearing at a specific structural position. A character-component generation model is presented to reduce component recognition error rate and accelerate the recognition process. Experimental results on MRG-OHTC database show that the proposed method gives promising performance comparing with the holistic method and the component-based conventional path evaluation method. © 2012 IEEE. |
| Keyword | Random Processes |
| Sponsorship | Presidenza del Consiglio dei Ministri; Governo Italiano; Ministero dello Sviluppo Economico; IAPR; Rete Puglia |
| Language | 英语 |
| Content Type | 会议论文 |
| URI | http://ir.iscas.ac.cn/handle/311060/15911 |
| Collection | 中国科学院软件研究所 |
| Recommended Citation GB/T 7714 | Ma Long-Long,Wu Jian. a component-based on-line handwritten tibetan character recognition method using conditional random field[C],2012:704-709. |
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