Abstract
A kind of optimal membership function is decided experimentally, which generates a fuzzy feature from the mesh pattern of character. This decision is based on the fact that the meshes with smaller number of black pixels is greater than those meshes with bigger one. According to experiments, it is confirmed that some of handwriting variations can be absorbed by fuzzification of the mesh feature. And the recognition rate can be improved about 4.9% by setting bigger membership value to those meshes with smaller number of black pixels when a character includes more of such kind of meshes. Moreover, when the fuzzy feature is applied to the near degree method with cutting value, the recogniton rate is additionally enhanced about 4.4%.
