An Improved Learning Scheme for the Moving Window Classifier for Handwritten Character Recognition

Hoque, Sanaul and Fairhurst, Michael (2001) An Improved Learning Scheme for the Moving Window Classifier for Handwritten Character Recognition. In: Document Analysis and Recognition, 2001. Proceedings. Sixth International Conference on. Sixth International Conference on document Analysis and Recognition, 1. IEEE computer society pp. 607-611. ISBN 0-7695-1263-1. (The full text of this publication is not available from this repository)

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Official URL
http://dx.doi.org/10.1109/ICDAR.2001.953861

Abstract

The Moving Window Classijier (MWC) is a simple and eficient classifier structure which, although shown to be capable of promising performance in a variety of tasks such as face recognition, its common application is a tool in text recognition. Various measures have been proposed to improve the MWC classification speed and to reduce memory space requirement. This paper introduces techniques for improving the MWC classification accuracy without losing any of gains previously achieved. These performance enhancement schemes ure readily applicable to a range of related classijiers and hence provide a generalized method for enhancement in a variety of tasks.

Item Type: Conference or workshop item (Paper)
Subjects: T Technology > TA Engineering (General). Civil engineering (General) > TA1637 Image Analysis, Image Processing
Divisions: Faculties > Science Technology and Medical Studies > School of Engineering and Digital Arts > Image and Information Engineering
Depositing User: Yiqing Liang
Date Deposited: 11 Aug 2009 09:26
Last Modified: 19 May 2014 11:36
Resource URI: http://kar.kent.ac.uk/id/eprint/6472 (The current URI for this page, for reference purposes)
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