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Artificial Neural Network Based Optical Character Recognition

Author(s): Vivek Shrivastava | Navdeep Sharma

Journal: Signal & Image Processing
ISSN 2229-3922

Volume: 3;
Issue: 5;
Start page: 73;
Date: 2012;
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Keywords: Feature Extraction | Vector Generation | Correlation Coefficients | Artificial Neural Networks | Walsh Hadamard Transform.

Optical Character Recognition deals in recognition and classification of characters from an image. For the recognition to be accurate, certain topological and geometrical properties are calculated, based on which a character is classified and recognized. Also, the Human psychology perceives characters by its overall shape and features such as strokes, curves, protrusions, enclosures etc. These properties, also calledFeatures are extracted from the image by means of spatial pixel-based calculation. A collection of such features, called Vectors, help in defining a character uniquely, by means of an Artificial Neural Network that uses these Feature Vectors.
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