Research on product image form optimization design

In order to design the products that meet consumer emotional demands, this paper proposes a systematic method which combines neural network with genetic algorithm. Firstly, a back propagation neural network is applied to map the relationships between product design elements and customer kansei image evaluation. Secondly, generic algorithm is employed to search for the optimal product form which satisfies customer requirement by using the trained neural network. Thirdly, the framework of product image form optimization design system based on VRML is analyzed. Finally, an example of kettle design is used to study, and the results show that this method is valid and feasible.