Online handwriting recognition: The NPen++ recognizer

被引：155

作者：

Jaeger S. ^{[1
,2
]}

Manke S. ^{[1
,2
]}

Reichert J. ^{[1
,2
]}

Waibel A. ^{[1
,2
]}

机构：

[1] Interactive Systems Laboratories, University of Karlsruhe, Computer Science Department

[2] Interactive Systems Laboratories, Carnegie Mellon University, School of Computer Science, Pittsburgh

来源：

International Journal on Document Analysis and Recognition | 2001年 / Springer Verlag卷 / 03期

关键词：

Human-computer interaction; Neural networks; Online handwriting recognition; Pattern recognition; Pen-based computing;

D O I：

10.1007/PL00013559

中图分类号：

TN7 [基本电子电路];

学科分类号：

080902 ;

摘要：

This paper presents the online handwriting recognition system NPen++ developed at the University of Karlsruhe and Carnegie Mellon University. The NPen++ recognition engine is based on a multi-state time delay neural network and yields recognition rates from 96% for a 5,000 word dictionary to 93.4% on a 20,000 word dictionary and 91.2% for a 50,000 word dictionary. The proposed tree search and pruning technique reduces the search space considerably without losing too much recognition performance compared to an exhaustive search. This enables the NPen++ recognizer to be run in real-time with large dictionaries. Initial recognition rates for whole sentences are promising and show that the MS-TDNN architecture is suited to recognizing handwritten data ranging from single characters to whole sentences. © 2001 Springer-Verlag Berlin Heidelberg.

引用

页码：169 / 180

页数：11

共 23 条

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