Lexicon-driven handwritten word recognition using optimal linearcombinations of order statistics
Chen, W.-T.
Gader, P.
Shi, H.
Dept. of Electr. Eng., Missouri Univ., Columbia, MO;
This paper appears in: Pattern Analysis and Machine Intelligence, IEEE Transactions on
Publication Date: Jan 1999
Volume: 21,
Issue: 1
On page(s): 77-82
ISSN: 0162-8828
References Cited: 31
CODEN: ITPIDJ
INSPEC Accession Number: 6171842
Digital Object Identifier: 10.1109/34.745738
Current Version Published: 2002-08-06
Abstract
In the standard segmentation-based approach to handwritten word
recognition, individual character-class confidence scores are combined
via averaging to estimate confidences in the hypothesized identities for
a word. We describe a methodology for generating optimal linear
combination of order statistics operators for combining character class
confidence scores. Experimental results are provided on over 1000 word
images
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