KNOWLEDGE MODEL-BASED APPROACH IN RECOGNITION OF ONLINE CHINESE CHARACTERS

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Please use this identifier to cite or link to this item: http://ir.lib.ncu.edu.tw/handle/987654321/29238

Title:	KNOWLEDGE MODEL-BASED APPROACH IN RECOGNITION OF ONLINE CHINESE CHARACTERS
Authors:	CHOU,KS;FAN,KC;FAN,TI;LIN,CK;JENG,BS
Contributors:	資訊工程研究所
Keywords:	ONLINE RECOGNITION
Date:	1994
Issue Date:	2010-06-29 20:17:12 (UTC+8)
Publisher:	中央大學
Abstract:	A knowledge model-based OCR system is presented in this study for the recognition of on-line connected stroke Chinese characters, In our approach, segment attributes are first extracted to characterize the segment sequence of an unknown character, Next, radical recognition based on model matching is adopted as the coarse classification to reduce the number of candidate characters before detailed matching, Finally, a deviation modeling method is proposed to recognize not only regular writing characters but also characters with stroke-order and stroke-number deviations, The effectiveness of the approach is verified by experiments on the recognition of on-line Chinese characters.
Relation:	IEEE JOURNAL ON SELECTED AREAS IN COMMUNICATIONS
Appears in Collections:	[Graduate Institute of Computer Science and Information Engineering] journal & Dissertation

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