DocumentCode
284896
Title
A fuzzy approach to hand-written rotation-invariant character recognition
Author
Wang, Li-Xin ; Mendel, Jerry M.
Author_Institution
Dept. of Electr. Eng.-Syst., Univ. of Southern California, Los Angeles, CA, USA
Volume
3
fYear
1992
fDate
23-26 Mar 1992
Firstpage
145
Abstract
A novel approach based on fuzzy set theory is developed for recognizing handwritten rotated characters. This fuzzy approach consists of four steps: (1) generating crisp sets for reference characters rotated through different degrees; (2) fuzzifying these crisp sets; (3) determining the degrees of a given character to the fuzzy sets; and (4) classifying the given character based on an average rule or a maximum rule. Simulation results show that the fuzzy approach correctly classified 94% to 100% of a small test set of characters
Keywords
character recognition; fuzzy set theory; average rule; character classification; fuzzy set theory; handwritten rotated characters recognition; maximum rule; reference characters; simulation; Character recognition; Fuzzy neural networks; Fuzzy set theory; Fuzzy sets; Image processing; Lattices; Neural networks; Pattern recognition; Signal processing; Testing;
fLanguage
English
Publisher
ieee
Conference_Titel
Acoustics, Speech, and Signal Processing, 1992. ICASSP-92., 1992 IEEE International Conference on
Conference_Location
San Francisco, CA
ISSN
1520-6149
Print_ISBN
0-7803-0532-9
Type
conf
DOI
10.1109/ICASSP.1992.226255
Filename
226255
Link To Document