Abstract :
In this paper a structure for a contextual cursive script recognition system is presented. This system makes use of letter context to determine word length, letter segmentation, and character identity to achieve contextual recognition at the word level. The system consists of a character recognizer that presents a set of best alternatives for each character to a contextual postprocessor whose task it is to determine the correct word.
Keywords :
Admissible sequence, binary diagram, context, correlator, cursive script, dictionary, likelihood ratio, Neyman-Pearson, pattern recognition, segment mark, substitution set.; Application software; Character recognition; Correlators; Dictionaries; Feature extraction; Optical character recognition software; Pattern recognition; Printing; Speech recognition; Statistics; Admissible sequence, binary diagram, context, correlator, cursive script, dictionary, likelihood ratio, Neyman-Pearson, pattern recognition, segment mark, substitution set.;
