Advances in International Computer Science

The rapid development of machine writing technology has brought new challenges to the authentication of handwriting authenticity. To recognize the handwriting imitated by the machine, it is necessary to construct a suitable classification model based on the visual and motion features. This paper systematically reviews the research progress in this field, focusing on the main recognition methods based on image analysis and motion modeling, and discusses their advantages and limitations. On this basis, a framework of machine handwriting detection system combining expert knowledge is proposed, and the possible challenges and limitations of this framework in practical application are discussed. By constructing expert knowledge base and rule engine, the integration of data driven and knowledge driven can be realized in order to obtain more comprehensive and reliable judgment results. Finally, the paper discusses the future improvement direction, including expanding the data set, refining the motor cognitive modeling, mining new physicochemical characteristics, etc., to provide reference for the realization of trusted human-machine writing environment.

Machine handwriting; Handwriting identification; Expert knowledge; Image analysis; Motion mode-ling