The behavior of dynamic relaxation in an elastic stroke model for character recognition

The paper presents an offline handwritten character recognition method based on a dynamic system. The method employs rubber string models for standard character patterns (called an “elastic stroke model”) and matches them with the potential field made from an input pattern. The matching process is realized by a dynamic relaxation with DP algorithm which minimizes the dynamic energy of rubber and potential field. To study the effect of the local minimum problem inherent in the relaxation technique, we used an improved DP method implemented on a parallel machine to compute the global minimum. Some experiments are performed on the 10 sets of 46 categories from the Japanese set of Hiragana characters that come from the ETL8b2c database. As a result, it is shown that the local minimum has little influence on recognition rates in this method, and the elastic stroke model could absorb deformation of character patterns