A feature curve-based method for balancing brand identity and emotional imagery in automobile frontal form design

Abstract

Automobile frontal forms are crucial for conveying form imagery and inheriting brand identity. However, few studies have balanced both brand features and form imagery. This research introduces a method for blending and recombining feature curves to achieve this balance. This method constructs a form database by extracting the form curves from numerous car frontal images and setting target imagery based on designers’ evaluations. Consumer perceptual questionnaires are then used to select base and reference forms from the database, which are decomposed into paired feature curves. Subsequently, new feature curves are generated using an improved ray-firing method and form blending algorithm. Three groups of form curves (group_1, group_2 and group_3) are created as alternatives through three recombination methods (method_1, method_2 and method_3) and converted into 3D renderings using image-generative AI. Finally, the alternatives are evaluated for brand form feature inheritance, form imagery transfer, and form aesthetics using the AHP, quadratic curvature entropy, and perceptual questionnaires. Results show that blending and recombining feature curves can effectively balance brand identity and emotional imagery, with quadratic curvature entropy serving as a reliable metric for assessing form aesthetics. This research offers an innovative approach to automobile form design, contributing to the advancement of the automotive industry.