Paper Info
Title
How to Improve a Handwriting Recognition System
Abstract
The recognition of handwritten characters, words, and text arouses great interest today. To develop the best working system is subject of many papers published. With this paper, methods to improve the performance of existing word recognition systems are discussed. The availability of a sufficient data sets for training and testing the system assumed, optimization algorithms are presented. The usage of different feature sets and the combination of different recognizers are proposed. Tests with Arabic handwriting recognition systems using the reference IfN/ENIT-database show the usefulness of the proposed methods. An improvement of the recognition rate of up to 28% of the best single system is achieved.
Year
DOI
Venue
2009
10.1109/ICDAR.2009.11
ICDAR-1
Keywords
Field
DocType
word recognition,text analysis,pixel,hidden markov models,database system,handwriting recognition,system testing,availability,feature extraction,noise reduction,communications technology
Data set,Computer science,Handwriting recognition,Artificial intelligence,Natural language processing,Intelligent word recognition,Intelligent character recognition,Pattern recognition,System testing,Word recognition,Feature extraction,Speech recognition,Hidden Markov model
Conference
ISSN
ISBN
Citations 
1520-5363 E-ISBN : 978-0-7695-3725-2
978-0-7695-3725-2
3
PageRank 
References 
Authors
0.39
12
3
Name
Order
Citations
PageRank
Haikal El-Abed143629.39
Volker Märgner229529.02
Haikal El-Abed325612.91