Representation and recognition of handprinted Chinese characters by string-matching

Robert I. Chou, Aaron Kershenbaum, Edward K. Wong

    Research output: Contribution to journalArticle


    This paper describes an optical recognition system for the handprinted Chinese characters. It is based on a novel string representation method and an inductive learning scheme that allows flexible (or elastic) representation and matching of unknown character instances. The system scans a character instance from four different views to obtain its peripheral segment information. A string representation is designed for representing the peripheral information at each of the four views. This representation can be generalized to represent the variations in different instances of a character by using an inductive learning algorithm. A clustering algorithm is developed to group the learned representation of characters into clusters in a hierarchical tree structure. Finally, a two-stage recognition process based on the developed representation is described. Experimental results demonstrate that high recognition rates can be obtained using the developed method.

    Original languageEnglish (US)
    Pages (from-to)1-34
    Number of pages34
    JournalInformation Sciences
    Issue number1-2
    StatePublished - Jan 1 1993

    ASJC Scopus subject areas

    • Software
    • Control and Systems Engineering
    • Theoretical Computer Science
    • Computer Science Applications
    • Information Systems and Management
    • Artificial Intelligence

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