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    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:[資訊工程研究所] 期刊論文

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