Title :
Lexicon-driven handwritten word recognition using optimal linear combinations of order statistics
Author :
Chen, Wen-Tsong ; Gader, Paul ; Shi, Hongchi
Author_Institution :
Dept. of Electr. Eng., Missouri Univ., Columbia, MO, USA
fDate :
1/1/1999 12:00:00 AM
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
Keywords :
dynamic programming; handwritten character recognition; statistics; character class confidence scores; lexicon-driven handwritten word recognition; optimal linear combinations; order statistics; Character generation; Character recognition; Computer Society; Handwriting recognition; Image segmentation; Law; Legal factors; Optimization methods; Statistics; Testing;
Journal_Title :
Pattern Analysis and Machine Intelligence, IEEE Transactions on
