Abstract: In order to uncover the intrinsic relationship between Chinese fonts and the emotional image of audience, this paper attempts to establish a grey box correlation model of design features-structure indexes-images to calculate multiple images of Chinese fonts from the perspective of cognitive psychology. Firstly, based on the theory of cognitive computing, the font structure rules were abstracted into knowledge. The production rules were applied to quantitatively describe the font structure knowledge, and the cognitive calculation formulas of four font structure indexes were proposed, namely, font weight, center of gravity, font circumscribed polygon, and font blank, which transform disordered morphological information into structured ordered information. Then based on the nonlinear coupling system characteristics of Chinese fonts image cognition, a multi-image prediction method of Chinese fonts was developed using multi-output least squares support vector regression machine (MLS-SVR). A method for multi-image prediction of Chinese fonts using MLS-SVR was developed to predict three images of Chinese fonts. The experimental results show that it is characteristic of good prediction bility and accuracy. The model can serve as the fitness function of the font intelligent design system, and provide a useful reference for the development of font intelligent design.

Key words: Chinese fonts, font structure indexes, multi-image, cognitive computing, MLS-SVR