Preliminary results of experiments with computer recognition of handwritten Hebrew characters are presented. The features used for the classification were the number of line crossings along some specified intersections, and the relative lengths of horizontal and vertical segments. Characters were clustered, first, according to some geometrical properties. Test characters within each cluster were then classified considering only those characters of the training set which were assigned to the same cluster. A min-Max decision rule yielded 90.9 percent of correct classification.
- Character recognition
ASJC Scopus subject areas
- Control and Systems Engineering
- Signal Processing
- Computer Vision and Pattern Recognition
- Electrical and Electronic Engineering