A Fuzzy Statistical Rule Generation Method for Handwriting Recognition
Liliane Peters, Christoph Leja, Ashutosh Malaviya · Expert Systems · 1998
This paper presents a statistical approach for rule‐base generation of handwriting recognition. The proposed method integrates the heuristic feature selection with the statistical evaluation and thus improves the performance of the rule generation as well as of the fuzzy handwriting recognition system. Fuzzy statistical measures are employed to identify relevant features from a given large handwriting database. First an automatic rule‐base mechanism is presented. To reduce the time needed for this generation mechanism an additional heuristic feature selection step is introduced. Tests show that this generated rule‐base improved the recognition results over previous approaches.