Image iterative method for handwritten Chinese character recognition

Abstract

Abstract Although accuracy and calculation time of handwritten Chinese character recognition have been greatly improved, it has not yet reached the practical application standard. Recently literatures, iterative method is used to recognize face images and good results are obtained. Therefore, image recognition is improved based on this idea. In this paper, linear combination of trigonometric functions is used as auxiliary function and image to construct discrete dynamic system. By adding bevel and shift to construct font surface and so on, the system structure is improved to solve problem of system convergence caused by large area flatness of handwritten Chinese character image, and good recognition effect is achieved. Preliminary experiments(for example, extracting 20 Chinese characters written by 9 people in the data set) are carried out, and recognition rate can reach 100% when all of them are trained, and recognition rate can reach 76.7% when each Chinese character is trained to 3 pieces; in addition, experiments were conducted on handwritten Chinese character sets changing from different angles, and the recognition rate reached 80%, which was compared with other algorithms to verify the feasibility of handwritten Chinese character recognition algorithm based on chaotic iterative trajectory characteristics of images.