Template-based online character recognition

被引：96

作者：

Connell, SD ^{[1
]}

Jain, AK ^{[1
]}

机构：

[1] Michigan State Univ, Dept Comp Sci & Engn, E Lansing, MI 48824 USA

来源：

PATTERN RECOGNITION | 2001年 / 34卷 / 01期

关键词：

clustering; string matching; online handwriting; prototypes; decision trees;

D O I：

10.1016/S0031-3203(99)00197-1

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

Handwriting is a common, natural form of communication for humans, and therefore it is useful to utilize this modality as a means of input to machines. One well-known method of classifying individual characters or words is template matching. We demonstrate a template-based system for online character recognition where the number of representative templates is determined automatically. These templates can be viewed as representing different styles of writing a particular character. The templates are then used as a reference for efficient classification using decision trees. Overall, our classifier achieves an 86.9% accuracy on a set of 17,928 alphanumeric characters (36 classes; 10 digits and 26 lowercase letters) with a throughput of over 8 characters per second on a 296 MHz Sun UltraSparc. (C) 2000 Pattern Recognition Society. Published by Elsevier Science Ltd. All rights reserved.

引用

页码：1 / 14

页数：14

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