Artificial Neural Network-Based Color Contrast Recommendation System

Abstract

Color contrast pertains to graphics and the field of design. Visual objects can be described nicely with the best contrast combinations used in their representation. Color contrast suggestion is usually done with color theory, which defines two colors exactly opposite or adjacent in color hue are good contrast with each other. Herein, this paper presents a Color Contrast Recommendation System (CCRS) as an innovative solution based on Artificial Neural Networks (ANN). The main aim of the paper is to facilitate different users to find suitable contrast for any base color. We used a simple neural network model with two hidden layers for a regression task. The proposed model suggests three contrast layers for the base color given by the user. We prepare a data set of 420 color combinations for training our Neural Network model that looks appealing together and enhances the visuals. The proposed color contrast recommendation application based on Neural Networks represents a significant advancement in leveraging AI technology to streamline the design process, improve accessibility, and enhance user experiences across digital platforms.

Keywords

• color contrast
• deep learning
• artificial neural network
• design recommendation
• and aesthetic appeal