Optical Character Recognition using 40-point Feature Extraction and Artificial Neural Network

We present in this paper a system of English handwriting recognition based on 40-point feature extraction of the character. Basically an off-line handwritten alphabetical character recognition system using multilayer feed forward neural network has been described in our work. Firstly a new method, called, 40-point feature extraction is introduced for extracting the features of the handwritten alphabets. Secondly, we use the data to train the artificial neural network. In the end, we test the artificial neural network and conclude that this method has a good performance at handwritten character recognition. This system will be suitable for converting handwritten documents into structural text form and recognizing handwritten names.

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