Research on color matching model for wood panel furniture based on a back propagation neural network

Abstract

The wood furniture manufacturing industry continues in the direction of customized furniture. The analysis of color collocation is important for developing customized furniture. This study summarizes the common color collocation application area for porch cabinets. After selecting the appropriate color model, C # language was used to simulate a real scene setting experimental system in the Unity graphics engine. Colors were generated randomly in the corresponding area, and subjects evaluated the harmony. Then, the Python language was used to build the BP neural network model. The BP neural network models were trained using the Hue, Saturation, value (HSV) of the depicted colors and their corresponding scores. Finally, the evaluation model of color collocation and harmony was obtained. The model can be used to improve the prediction of color matching in customized furniture, which will promote enterprise productivity and industry development.