DocumentCode
1102101
Title
A knowledge-based approach for script recognition without training
Author
Rao, P.V.S.
Author_Institution
Comput. Syst. & Commun. Group, Tata Inst. of Fundamental Res., Bombay, India
Volume
17
Issue
12
fYear
1995
fDate
12/1/1995 12:00:00 AM
Firstpage
1233
Lastpage
1239
Abstract
The approach described is based on an empirical parametric model for the handwriting recognition system. The parameters are so chosen and quantized as to retain only broad shape information, ignoring writer-dependent and other variability. Concatenation of character prototypes generates archetypal reference words for recognition, and training is unnecessary. The recognition scores exceed 90%
Keywords
character recognition; image coding; image segmentation; knowledge based systems; real-time systems; archetypal reference words; character recognition; cursive script recognition; decoding; empirical parametric model; encoding; handwriting recognition system; knowledge-based system; shape vectors; transition segments; Character generation; Character recognition; Decoding; Hidden Markov models; Parametric statistics; Pattern recognition; Prototypes; Shape; Transfer functions; Writing;
fLanguage
English
Journal_Title
Pattern Analysis and Machine Intelligence, IEEE Transactions on
Publisher
ieee
ISSN
0162-8828
Type
jour
DOI
10.1109/34.476518
Filename
476518
Link To Document