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Cascade Markov random fields for stroke extraction of Chinese characters
文献类型:期刊
作者:Zeng, Jia[1]  Feng, Wei[2]  Xie, Lei[3]  Liu, Zhi-Qiang[4]  
机构:[1]Department of Computer Science, Hong Kong Baptist University, Kowloon Tong, Hong Kong
[2]Department of Computer Science and Engineering, The Chinese University of Hong Kong, Shatin, N.T., Hong Kong
[3]School of Computer Science, Northwestern Polytechnical University, Xi'an, China
[4]School of Creative Media, City University of Hong Kong, Tat Chee Avenue 83, Hong Kong
通讯作者:Zeng, J (reprint author), Hong Kong Baptist Univ, Dept Comp Sci, Kowloon Tong, Hong Kong, Peoples R China.
年:2010
期刊名称:INFORMATION SCIENCES影响因子和分区
卷:180
期:2
页码范围:301-311
增刊:正刊
学科:计算机科学
收录情况:SCI(E)(WOS:000272289100008)  EI(20094512432229)  
所属部门:计算机学院
被引频次:8
人气指数:4293
浏览次数:4257
关键词:Stroke extraction; Cursive Chinese characters; Cascade Markov random fields; Bottom-up/top-down
摘要:
Extracting perceptually meaningful strokes plays an essential role in modeling structures of handwritten Chinese characters for accurate character recognition. This paper proposes a cascade Markov random field (MRF) model that combines both bottom-up (BU) and top-down (TD) processes for stroke extraction. In the low-level stroke segmentation process, we use a BU MRF model with smoothness prior to segment the character skeleton into directional substrokes based on self-organization of pixel-based ...More
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