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a component-based on-line handwritten tibetan character recognition method using conditional random field
Ma Long-Long; Wu Jian
2012
Conference Name13th International Conference on Frontiers in Handwriting Recognition, ICFHR 2012
SourceProceedings - International Workshop on Frontiers in Handwriting Recognition, IWFHR
Pages704-709
Conference DateSeptember 18, 2012 - September 20, 2012
Conference PlaceBari, Italy
Indexed TypeEI
ISSN1550-5235
ISBN9780769547749
Department(1) National Engineering Research Center of Fundamental Software Institute of Software Chinese Academy of Sciences Beijing China
English AbstractThis 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.
KeywordRandom Processes
SponsorshipPresidenza del Consiglio dei Ministri; Governo Italiano; Ministero dello Sviluppo Economico; IAPR; Rete Puglia
Language英语
Content Type会议论文
URIhttp://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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