DocumentCode
2613728
Title
Character recognition using neural based feature extractor and classifier
Author
Cao, J. ; Ahmadi, M. ; Shridhar, M.
Author_Institution
Dept. of Electr. Eng., Windsor Univ., Ont., Canada
fYear
1993
fDate
3-6 May 1993
Firstpage
2442
Abstract
The authors present a neural network architecture for the recognition of handwritten digits and machine printed multi-font characters. To reduce the dimension of the input data vector as well as robustness of the system, an appropriate neural net is utilized for the feature extraction part which is cascaded with another neural net for the classification purpose. The proposed architecture has been tested on a large sample of real field data and the results indicate the effectiveness of the proposed technique
Keywords
character recognition; character sets; feature extraction; neural nets; pattern classification; classification; handwritten digits; input data vector; machine printed multi-font characters; neural based feature extractor; neural network architecture; robustness; Character recognition; Computer architecture; Data mining; Feature extraction; Handwriting recognition; Neural networks; Personal communication networks; Principal component analysis; Robustness; Testing;
fLanguage
English
Publisher
ieee
Conference_Titel
Circuits and Systems, 1993., ISCAS '93, 1993 IEEE International Symposium on
Conference_Location
Chicago, IL
Print_ISBN
0-7803-1281-3
Type
conf
DOI
10.1109/ISCAS.1993.394258
Filename
394258
Link To Document