A Serial combination of neural network for arabic OCR
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Date
2014
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Publisher
Springer
Abstract
Today, handwriting recognition is one of the most challenging
tasks and exciting areas of search in computer science. Indeed, despite
the growing interest in this field, no satisfactory solution is available. For
this reason Multiple Classifier Systems (MCS) based on the combination
of outputs of a set of different classifiers have been proposed as a method
for the developing of high performance classifier system. In this paper
we describe a serial combination scheme of an Arabic Optical Character
Recognition System. The classification engine is based on Adaptive
Resonance Theory and Radial Basic Function, where an RBF network
acting as the first classifier is properly combined with a set of ART1
network (one for each group) trained to classify the word image. The
experiments applied on the IFN/ENIT database show that the proposed
architecture exhibits best performance
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Keywords
Arabic recognition, Serial combination, Radial basic function, Adaptive resonance theory