DocumentCode
1341185
Title
Multi-prototype classification: improved modelling of the variability of handwritten data using statistical clustering algorithms
Author
Rahman, A.F.R. ; Fairhurst, M.C.
Author_Institution
Electron. Eng. Labs., Kent Univ., Canterbury, UK
Volume
33
Issue
14
fYear
1997
fDate
7/3/1997 12:00:00 AM
Firstpage
1208
Lastpage
1210
Abstract
The principal obstacle in successfully recognising handwritten data is the inherent degree of intra-class variability encountered. This calls for subclass modelling of handwritten data based on the statistically significant variations within the main classes. A novel multi-prototyping approach based on statistical clustering techniques is investigated as an appropriate solution to this problem and very encouraging results have been achieved
Keywords
handwriting recognition; pattern classification; real-time systems; statistical analysis; handwritten data; intra-class variability; multi-prototype classification; statistical clustering algorithms; subclass modelling; variability modelling;
fLanguage
English
Journal_Title
Electronics Letters
Publisher
iet
ISSN
0013-5194
Type
jour
DOI
10.1049/el:19970848
Filename
603574
Link To Document