A GENERALIZED KNOWLEDGE-BASED SYSTEM FOR THE RECOGNITION OF UNCONSTRAINED HANDWRITTEN NUMERALS

被引:27
作者
MAI, TA [1 ]
SUEN, CY [1 ]
机构
[1] CONCORDIA UNIV,DEPT COMP SCI,CTR PATTERN RECOGNIT & MACHINE INTELLIGENCE,MONTREAL H3G 1M8,QUEBEC,CANADA
来源
IEEE TRANSACTIONS ON SYSTEMS MAN AND CYBERNETICS | 1990年 / 20卷 / 04期
基金
加拿大自然科学与工程研究理事会;
关键词
D O I
10.1109/21.105083
中图分类号
TP3 [计算技术、计算机技术];
学科分类号
0812 ;
摘要
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 17 000 totally unconstrained handwritten numerals are presented. The performance of the system under different recognition-rejection trade-off ratios is analyzed in detail. © 1990 IEEE
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页码:835 / 848
页数:14
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