Benefit of multiclassifier systems for Arabic handwritten words recognition

In order to improve the results of single classifiers, the study of multiple classifier systems has become an area of intensive research in pattern recognition. In this paper, two types of features are fed to a number of artificial neural networks (ANN). Then, their respective responses are combined for the recognition of handwritten Arabic literal words. Different parallel combination schemes are presented, including the use of an ANN as a meta classifier. Their results are then compared and conclusions on the most suitable approach are drawn.