![]() Then at the hidden layer centers are determined and the weights between the hidden layer and the output layer of each neuron are determined to calculate the output, where output is the summing value of each neuron. Since different people have different writing style, so here we are trying to form a system where recognition of numeral becomes easy. Then by the use of Principal Component Analysis we have extracted the features of each image, some researchers have also used density feature extraction. Designing stencil font in Devanagari script. ![]() Since the database is not globally created, firstly we created the database by implementing pre-processing on the set of training data. Lot of work has been done on Devanagari numeral recognition using different techniques for increasing the accuracy of recognition. This paper applies the technique of Radial Basis Function for handwritten numeral recognition of Devanagari Script. In India, Devanagari is the basic script of many languages like Sanskrit and Hindi. The task of recognizing handwritten numerals, using a classifier, has great importance. Introduction of Devanagari Script After English and Chinese, Hindi is the third most widely used language and all over the world, there are approximately 500 billion people who write and speak Hindi. ![]()
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