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Nonlinear and Non-Gaussian Bayesian Based Handwriting Beautification
Shi, Cao ; Xiao, Jianguo ; Xu, Canhui ; Jia, Wenhua
2014
关键词Handwriting beautification Bayesian statistics optimization typeface CHINESE CALLIGRAPHIC WRITINGS AUTOMATIC-GENERATION BRUSH MODEL
英文摘要A framework is proposed in this paper to effectively and efficiently beautify handwriting by means of a novel nonlinear and non-Gaussian Bayesian algorithm. In the proposed framework, format and size of handwriting image are firstly normalized, and then typeface in computer system is applied to optimize vision effect of handwriting. The Bayesian statistics is exploited to characterize the handwriting beautification process as a Bayesian dynamic model. The model parameters to translate, rotate and scale typeface in computer system are controlled by state equation, and the matching optimization between handwriting and transformed typeface is employed by measurement equation. Finally, the new typeface, which is transformed from the original one and gains the best nonlinear and non-Gaussian optimization, is the beautification result of handwriting. Experimental results demonstrate the proposed framework provides a creative handwriting beautification methodology to improve visual acceptance.; http://gateway.webofknowledge.com/gateway/Gateway.cgi?GWVersion=2&SrcApp=PARTNER_APP&SrcAuth=LinksAMR&KeyUT=WOS:000335494800029&DestLinkType=FullRecord&DestApp=ALL_WOS&UsrCustomerID=8e1609b174ce4e31116a60747a720701 ; Optics; Imaging Science & Photographic Technology; EI; CPCI-S(ISTP); 0
语种英语
DOI标识10.1117/12.2040160
内容类型其他
源URL[http://ir.pku.edu.cn/handle/20.500.11897/321142]  
专题信息科学技术学院
推荐引用方式
GB/T 7714
Shi, Cao,Xiao, Jianguo,Xu, Canhui,et al. Nonlinear and Non-Gaussian Bayesian Based Handwriting Beautification. 2014-01-01.
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