DocumentCode
2628884
Title
Totally unconstrained handwritten numeral recognition via fuzzy graphs
Author
Abuhaiba, I.S.I. ; Ahmed, P.
Author_Institution
King Saud Univ., Riyadh, Saudi Arabia
fYear
1993
fDate
20-22 Oct 1993
Firstpage
846
Lastpage
849
Abstract
The performance of a novel recognition system which uses fuzzy constrained character graph models (FCCGMs) is investigated for totally unconstrained and handwritten numeral recognition. The system was tested on 1812 unnormalized samples. The reliability, recognition, substitution error, and rejection rates of the system were 97.1%, 90.7%, 2.9%, and 6.4%, respectively
Keywords
fuzzy set theory; graph theory; handwriting recognition; optical character recognition; fuzzy constrained character graph models; novel recognition system; substitution error; unconstrained handwritten numeral recognition; unnormalized samples; Character generation; Character recognition; Computer science; Data mining; Error analysis; Fuzzy sets; Handwriting recognition; Humans; Optical wavelength conversion; Phase measurement;
fLanguage
English
Publisher
ieee
Conference_Titel
Document Analysis and Recognition, 1993., Proceedings of the Second International Conference on
Conference_Location
Tsukuba Science City
Print_ISBN
0-8186-4960-7
Type
conf
DOI
10.1109/ICDAR.1993.395605
Filename
395605
Link To Document