A color-pair based approach for accurate color harmony estimation.

Abstract

Harmonious color combinations can stimulate positive user emotional responses. However, a widely open research question is: how can we establish a robust and accurate color harmony measure for the public and professional designers to identify the harmony level of a color theme or color set. Building upon the key discovery that color pairs play an important role in harmony estimation, in this paper we present a novel color-pair based estimation model to accurately measure the color harmony. It first takes a two-layer maximum likelihood estimation (MLE) based method to compute an initial prediction of color harmony by statistically modeling the pair-wise color preferences from existing datasets. Then, the initial scores are refined through a back-propagation neural network (BPNN) with a variety of color features extracted in different color spaces, so that an accurate harmony estimation can be obtained at the end. Our extensive experiments, including performance comparisons of harmony estimation applications, show the advantages of our method in comparison with the state of the art methods.