Mohammad R. Moradian

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A method for recognition of Persian handwritten digits based on characterization loci and mixture of experts is proposed. This method utilizes the characterization loci, as the main feature. In the classification stage of our proposed method the mixture of experts are applied. This recognition method is applied to Farsi handwritten digits in the HODA(More)
In this paper a binary decision tree, based on Neural Networks, Support Vector Machine and K-Nearest Neighbor is employed and presented for recognition of Persian handwritten isolated digits and characters. In the proposed method, a part of the training data is divided into two clustersusing a clustering algorithm, and this process continues until each(More)
The present work is concerned with handwritten and printed numeral recognition based on an improved version of the loci characteristic method (CL) for extracting the numeral features. After a preprocessing of the numeral image, the method divides the image into four equal parts and applies the traditional CL to each of the parts. The recognition rate(More)
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