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Lexicon-driven handwritten word recognition using optimal linear combinations of order statistics

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3 Author(s)
W. -T. Chen ; Dept. of Electr. Eng., Missouri Univ., Columbia, MO, USA ; P. Gader ; H. Shi

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

Published in:

IEEE Transactions on Pattern Analysis and Machine Intelligence  (Volume:21 ,  Issue: 1 )