ONLINE RECOGNITION BY DEVIATION-EXPANSION MODEL AND A-ASTERISK ALGORITHM-BASED MATCHING

NCUIR > College of Electrical Engineering & Computer Science > Graduate Institute of Computer Science and Information Engineering > journal & Dissertation > Item 987654321/29247

Please use this identifier to cite or link to this item: http://ir.lib.ncu.edu.tw/handle/987654321/29247

Title:	ONLINE RECOGNITION BY DEVIATION-EXPANSION MODEL AND A-ASTERISK ALGORITHM-BASED MATCHING
Authors:	LIN,CK;FAN,KC;LEE,FTP
Contributors:	資訊工程研究所
Date:	1993
Issue Date:	2010-06-29 20:17:27 (UTC+8)
Publisher:	中央大學
Abstract:	This paper presents an online recognition system for large-alphabet handprinted Chinese characters using a model-based recognition approach with stroke-based features. A deviation-expansion (D-E) model representing the reference pattern is constructed. The model contains hypothetical knowledge of handwriting variations, including stroke-order deviations and stroke-number deviations. For pattern matching, a matching tree is constructed by combining the knowledge of the reference pattern and the unknown pattern together. With the tree a similarity measure function is defined to indicate the degree of similarity. Evaluation of the function is obtained using A* algorithm-based matching. Experimental results are based upon testing a set Of 54010 handprinted sample characters written in the square style by ten people. The cumulative classification rate of choosing the ten most similar characters is 98%. The results suggest that the hypothetical model is both feasible and reasonable.
Relation:	IMAGE AND VISION COMPUTING
Appears in Collections:	[Graduate Institute of Computer Science and Information Engineering] journal & Dissertation

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