Writer Recognition by Means of Fuzzy Theory

Abstract

A new off-line writer recognition method was proposed. In the methed, a 2-D membership function was obtained by piling up characters as a dictionary. The recognition procedure was a multi-character matching in which 4 types of characters were used. This was an extension of our previous work that was also used 2-D membership function with α-cut. In this paper, the principal component analysis was used to characterize one's hand writing features. The indivisual dictionary was obtained from characters which were not far from the average character. The proposed system was applied to writer recognition of 108 students who wrote 46 types of “hiragana” characters, in total 24, 840 characters, and fairly good results, almost 100% recognition rates, were obtained.