Research on Off-line Handwritten Chinese Characters Recognition Based on Biomimetic Pattern

Abstract

In this paper, the off-line Chinese character image is transformed into ellipse shape of basic Chinese characters strokes in different position. The stroke turning and joint or crossover of strokes is combined by basic strokes. The neural network for extracting Chinese character has been build up. The research on off-line Chinese character image is transformed into the research on double weights elliptical neural network based on biomimetic pattern. By extracting fault-tolerant features of the 4 kinds of basic stroke, 13 kinds of turning stroke and 7 kinds of consistency and intersection of strokes, the data-knowledge table of features is constructed. The method of bionic recognition gives the machine the ability of cognizing features of stroke type and number, features of stroke location and features of topology structural. The simple and complex handwritten Chinese characters are used to carry out simulation experiment in SCUT-IRAC-HCCLIB. The experiment results show that the algorithm exhibits a strong ability of cognizing handwritten Chinese characters.