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Author Wenwei Wang ♦ Brakensiek, A. ♦ Rigoll, G.
Sponsorship CEDAR, Univ. Buffalo ♦ Microsoft ♦ Siemens ♦ Hitachi ♦ Motorola ♦ U.S. Postal Service ♦ A2iA ♦ Int. Assoc. Pattern Recognition
Source IEEE Xplore Digital Library
Content type Text
Publisher Institute of Electrical and Electronics Engineers, Inc. (IEEE)
File Format PDF
Copyright Year ©2002
Language English
Subject Domain (in DDC) Technology ♦ Engineering & allied operations ♦ Other branches of engineering
Subject Keyword Handwriting recognition ♦ Voting ♦ Runtime ♦ Vocabulary ♦ Character recognition ♦ Computer science ♦ Man machine systems ♦ Shape ♦ Humans ♦ Error analysis
Abstract Due to large shape variations in human handwriting, recognition accuracy of cursive handwritten word is hardly satisfying using a single classifier. In this paper we introduce a framework to combine results of multiple classifiers and present an intuitive run-time weighted opinion pool combination approach for recognizing cursive handwritten words with a large size vocabulary. The individual classifiers are evaluated run-time dynamically. The final combination is weighted according to their local performance. For an open vocabulary recognition task, we use the ROVER algorithm to combine the different strings of characters provided by each classifier. Experimental results for recognizing cursive handwritten words demonstrate that our new approach achieves better recognition performance and reduces the relative error rate significantly.
Description Author affiliation: Dept. of Comput. Sci., Gerhard Mercator Univ., Duisburg, Germany (Wenwei Wang; Brakensiek, A.)
ISBN 0769516920
Educational Role Student ♦ Teacher
Age Range above 22 year
Educational Use Research ♦ Reading
Education Level UG and PG
Learning Resource Type Article
Publisher Date 2002-08-06
Publisher Place Canada
Rights Holder Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Size (in Bytes) 277.45 kB
Page Count 6
Starting Page 117
Ending Page 122


Source: IEEE Xplore Digital Library