A Hybrid Clustering-Based Approach to Color Modification of Art Paintings for Protanopes and Deuteranopes

Abstract

The normal human color vision is trichromatic, and it originates from the comparison of the rates at which photons are absorbed by three types of photoreceptor cone-cells contained in the eye's retina. The absence or malfunctioning of one or two types of cone results in color-blindness. This paper proposes an algorithmic framework to appropriately modify (i.e., recolor) art paintings for two types of color-blindness called protanopia and deuteranopia. The algorithmic framework employs four distinct steps applied in sequence. First, the image colors are clustered into a prespecified number of representative colors. The second step determines the representative colors that are confused by the protanopes or the deuteranopes. Third, an optimization problem is proposed to appropriately recolor the representative colors detected in the previous step. Finally, given the recolored representative colors, the original image pixels associated with those colors are also modified accordingly. The method is tested and evaluated in terms of quantitative, qualitative, and subjective comparison with three other recoloring algorithms. The results are promising in the sense that the proposed method outperforms the competitive algorithms, maintaining the overall aesthetic of the paintings.