Title :
Totally unconstrained handwritten numeral recognition via fuzzy graphs
Author :
Abuhaiba, I.S.I. ; Ahmed, P.
Author_Institution :
King Saud Univ., Riyadh, Saudi Arabia
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;
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
DOI :
10.1109/ICDAR.1993.395605
