A neural network classifier for OCR using structural descriptions
Identifieur interne : 002D19 ( Main/Merge ); précédent : 002D18; suivant : 002D20A neural network classifier for OCR using structural descriptions
Auteurs : P. Cordella [Italie] ; C. De Stefano [Italie] ; M. Vento [Italie]Source :
- Machine Vision and Applications [ 0932-8092 ] ; 1995-09-01.
Abstract
Abstract: We present a method for character recognition especially designed for the case in which the shapes of characters belonging to the same class vary greatly, as it happens with unconstrained hand-printed characters and omnifont printed characters. The most distinctive feature of the method is the use of a special kind of structural description of character shape in connection with a neural network classifier. An original technique is used to achieve the best trade-off between reject and misclassification rates. Experimental results on databases of both hand-printed and printed characters are illustrated.
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DOI: 10.1007/BF01211495
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