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A generalized knowledge-based system for the recognition of unconstrained handwritten numerals

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2 Author(s)
T. A. Mai ; Concordia Univ., Montreal, Que., Canada ; C. Y. Suen

A method of recognizing unconstrained handwritten numerals using a knowledge base is proposed. Features are collected from a training set and stored in a knowledge base that is used in the recognition stage. Recognition is accomplished by either an inference process or a structural method. The scheme is general, flexible, and applicable to different methods of feature extraction and recognition. By changing the acceptance parameters, a continuous range of performance can be achieved. Encouraging results on nearly 17000 totally unconstrained handwritten numerals are presented. The performance of the system under different recognition-rejection tradeoff ratios is analyzed in detail

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IEEE Transactions on Systems, Man, and Cybernetics  (Volume:20 ,  Issue: 4 )