DocumentCode
2737344
Title
Novel preprocessing techniques as an aid to hand-printed character recognition
Author
Stonham, T.J.
fYear
1991
fDate
8-14 Jul 1991
Abstract
Summary form only given. Two preprocessing techniques designed to greatly reduce the burden of classification on an artificial neural network have been developed. The first is a transform which is invariant to rotation, size, and breaks in characters. The second is a low-level feature extractor, in which the features have been statistically selected. The resulting output yields a 45% reduction in memory requirement without any degradation in recognition performance
Keywords
character recognition; neural nets; artificial neural network; classification; hand-printed character recognition; low-level feature extractor; memory requirement; preprocessing techniques; recognition performance; Artificial neural networks; Character recognition; Computer networks; Degradation; Feature extraction; Information processing;
fLanguage
English
Publisher
ieee
Conference_Titel
Neural Networks, 1991., IJCNN-91-Seattle International Joint Conference on
Conference_Location
Seattle, WA
Print_ISBN
0-7803-0164-1
Type
conf
DOI
10.1109/IJCNN.1991.155544
Filename
155544
Link To Document