A computational evaluation system of Chinese calligraphy via extended possibility-probability distribution method

Zhou, Dajun, Ge, Jiamin, Wu, Ruiqi, Chao, Fei, Yang, Longzhi and Zhou, Changle (2017) A computational evaluation system of Chinese calligraphy via extended possibility-probability distribution method. In: 2017 13th International Conference on Natural Computation, Fuzzy Systems and Knowledge Discovery (ICNC-FSKD). IEEE, pp. 884-889. ISBN 978-1-5386-2166-0

Full text not available from this repository.
Official URL: http://doi.org/10.1109/FSKD.2017.8393393

Abstract

Robotic calligraphy has became a popular research topic in robotics. Therefore, a computational calligraphy evaluation system is required to access the quality of robotic writing results. This paper applies three types of feature criteria, derived from Chinese calligraphy theories, to extract features of Chinese characters from Chinese Calligraphy textbooks. Then, the Possibility-Probability Distribution method deals with these extracted features, so as to obtain the feature distribution of quality handwriting characters. The Possibility-Probability Distribution method uses the extracted features to automatically build an interior-outer-set computational model based on information diffusion theory. When the computational model is established, each Chinese character, written by a robot, is also extracted to three features; then, the computational model estimates each character's evaluation value. The experimental results demonstrate that the proposed method successfully produces an interior-outer-set computational model from Chinese calligraphy books. In particular, the model is able to generate an evaluation result for each character written by a robot system. To check the validation of the computational model, these characters are also evaluated by human experts. The comparison shows that the evaluation results of human experts are very similar to that of the computational model.

Item Type: Book Section
Subjects: G400 Computer Science
Department: Faculties > Engineering and Environment > Computer and Information Sciences
Depositing User: Becky Skoyles
Date Deposited: 25 Jul 2018 15:00
Last Modified: 25 Jul 2018 15:00
URI: http://nrl.northumbria.ac.uk/id/eprint/35117

Actions (login required)

View Item View Item

Downloads

Downloads per month over past year

View more statistics


Policies: NRL Policies | NRL University Deposit Policy | NRL Deposit Licence