Recognition of Text Image Using Multilayer Perceptron
Singh Vijendra, Nisha Vasudeva, Hem Jyotsana Parashar

TL;DR
This paper presents a method for recognizing printed and handwritten text images using a multilayer perceptron neural network with back propagation, achieving character classification from scanned document images.
Contribution
It introduces a neural network-based approach employing multilayer perceptron and back propagation for effective text image recognition in printed and handwritten documents.
Findings
Successful recognition of characters from scanned images.
Effective classification using multilayer perceptron neural network.
Improved accuracy with back propagation training.
Abstract
The biggest challenge in the field of image processing is to recognize documents both in printed and handwritten format. Optical Character Recognition OCR is a type of document image analysis where scanned digital image that contains either machine printed or handwritten script input into an OCR software engine and translating it into an editable machine readable digital text format. A Neural network is designed to model the way in which the brain performs a particular task or function of interest: The neural network is simulated in software on a digital computer. Character Recognition refers to the process of converting printed Text documents into translated Unicode Text. The printed documents available in the form of books, papers, magazines, etc. are scanned using standard scanners which produce an image of the scanned document. Lines are identifying by an algorithm where we identify…
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Taxonomy
TopicsNeural Networks and Applications
