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The aim of this work is to present a system for recognizing isolated Arabic printed characters. This system goes through several stages: preprocessing, feature extraction and classification. Zernike moments, invariant moments and Walsh transformation are used to calculate the features. The classification is based on multilayer neural networks. A recognition(More)
Most of the reported works in the field of character recognition systems achieve modest results by using a single method for calculating the parameters of the character image and a single approach in the classification phase of the system. So, in order to improve the recognition rate, this document proposes an automatic system to recognize isolated printed(More)
This paper provides an approach to automatically recognize the Tifinagh characters. The proposed recognition system is based on Texture, Walsh transformation and GIST descriptors as feature extraction methods while the Bayesian Networks are used as a classifier. A comparative study between the Texture descriptor, Walsh transformation and GIST descriptor is(More)
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