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Recognition of Handwritten Character of Manipuri Script

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Author(s): Tangkeshwar Thokchom | P.K. Bansal | Renu Vig | Seema Bawa

Journal: Journal of Computers
ISSN 1796-203X

Volume: 5;
Issue: 10;
Start page: 1570;
Date: 2010;
Original page

Keywords: Binarisation | Segmentation | Feature extraction | Neural network | Fuzzy feature | Recognition

ABSTRACT
In this paper a backpropagation neural network based handwritten characters (Mapum Mayek ) recognition system of Manipuri Script is investigated. This paper presents various steps involved in the recognition process. It begins with thresholding of gray level image into binarised image, then from the binarised image the character pattern is segmented using connected component analysis and from the resized character matrix, its probabilistic features and fuzzy features are extracted. Using these features the network is trained and recognition tests are performed. Experiments indicate that the proposed recognition system performs well with the combined features and is robust to the writing variations that exist between persons and for a single person at different instances, thus being promising for user independent character recognition.
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