The Neural-based Segmentation of Cursive Words using Enhanced Heuristics

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Title The Neural-based Segmentation of Cursive Words using Enhanced Heuristics
Author Cheng, Chun Ki; Blumenstein, Michael Myer
Publication Title Proceedings of the Eighth International Conference on Document Analysis and Recognition
Editor Bob Werner
Year Published 2005
Place of publication Los Alamitos, CA, USA
Publisher IEEE Computer Society
Abstract This paper presents an enhanced heuristic segmenter (EHS) and an improved neural-based segmentation technique for segmenting cursive words and validating prospective segmentation points respectively. The EHS employs two new features, ligature detection and a neural assistant, to locate prospective segmentation points. The improved neural-based segmentation technique can then be used to examine the prospective segmentation points by fusion of confidence values obtained from left and centre character recognition outputs in addition to the segmentation point validation (SPV) output. The improved neural-based segmentation technique uses a recently proposed feature extraction technique (modified direction feature) for representing the segmentation points and characters to enhance the overall segmentation process. The EHS and the neural-based segmentation technique have been implemented and tested on a benchmark database providing encouraging results.
Peer Reviewed Yes
Published Yes
Alternative URI http://dx.doi.org/10.1109/ICDAR.2005.237
Copyright Statement Copyright 2005 IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE.
ISBN 0769524206
Conference name International Conference on Document Analysis and Recognition (ICDAR)
Location Seoul, Korea
Date From 2005-08-31
Date To 2005-09-01
URI http://hdl.handle.net/10072/2571
Date Accessioned 2006-03-15
Date Available 2010-10-13T09:58:59Z
Language en_AU
Research Centre Institute for Integrated and Intelligent Systems
Faculty Faculty of Engineering and Information Technology
Subject PRE2009-Pattern Recognition
Publication Type Conference Publications (Full Written Paper - Refereed)
Publication Type Code e1

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