A fast handwritten word recognition system for real time applications is presented. Preprocessing, segmentation and feature extraction are implemented using chain code representation. Dynamic matching between each character of a lexicon entry and segment(s) of input word image is used for ranking words in the lexicon. Speed of the entire recognition process is about 200 msec on a single SPARC-10 platform for lexicon size of 10. A top choice performance of 96% is achieved on a database of postal words captured at 212 dpi.
Handwritten word recognition for real-time applications
01.01.1995
384590 byte
Aufsatz (Konferenz)
Elektronische Ressource
Englisch
Handwritten Word Recognition for Real-Time Applications
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