Some remarks on the application of artificial neural networks to optical character recognition

Authors:
A. Moratilla;I. Olmeda
Affiliations:
Dpto. Ciencias de la Computación, Universidad de Alcalá, Spain;Dpto. Ciencias de la Computación, Universidad de Alcalá, Spain
Venue:
IWINAC'05 Proceedings of the First international work-conference on the Interplay Between Natural and Artificial Computation conference on Artificial Intelligence and Knowledge Engineering Applications: a bioinspired approach - Volume Part II
Year:
2005

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Abstract

In this paper we analyze one important aspect related to handwritten Optical Character Recognition, specifically, we demonstrate that the standard procedure of minimizing the number of misclassified characters could be inconsistent in some applications. To do so, we consider the problem of automatic reading of amounts written in bank cheques and show that the widely used confusion matrix does not provide an appropriate measure of the performance of a particular classifier. We motivate our approach with some examples and suggest a novel procedure, using real data, to improve the performance by considering the true economic costs of the expected misclassification errors.