Lexicon-driven handwritten word recognition using optimal linear combinations of order statistics
W.-T. Chen, Paul Gader, H. Shi · IEEE Transactions on Pattern Analysis and Machine Intelligence · 1999
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.