Comparison of feature performance and its application to feature combination in off-line handwritten korean alphabet recognition

摘要

This paper presents (1) a quantitative performance comparison of the features used in off-line handwritten Korean alphabet recognition, and (2) some experimental results based on the feature combination approach. We classified the features into three: geo- metrical/topological, statistical and global. For each class, we selected four of five fea- tures and performed recognition experiments with PE92 database using neural network classifiers. We compared their recognition performances and selected the top four among those thirteen features: Up Down Left Right Hole, Gradient, Structure, and Mesh.