Optical Character Recognition Using Artificial Neural Networks Approach
نویسندگان
چکیده
The recent advances in computer technology many recognition task have been automated. OCR, Optical Character Recognition is a scheme of converting the images of typewritten or printed text into a format that is understood by machine. The goal of OCR is to classify the given character data represented by some characteristics, into a predefined finite number of character classes. For the recognition to be precise certain topological and geometrical properties are calculated, on the basis of which characters are classified and recognized. These properties are called features and, the collection of such features is called vectors which help is defining the character uniquely. The main aim of this attempt is to explore the utility of Artificial Neural Networks based approach to the recognition of characters. A unique multilayer perception of neural network is built for classification using BackPropagation learning algorithm. Keywords— Artificial Neural Network, BackPropagation Algorithm, Multilayer Feed Forward Architecture, Optical Character Recognition, Pattern Recognition.
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