Color adaptation for protanopia using differential evolution-based fuzzy clustering: A case study in digitized paintings

Abstract

The daltonization process refers to the color adaptation of images in order to improve the perception of color-blind viewers. This paper proposes a modified clustering approach, which is applied to color adaptation of digitized art paintings and concerns a specific color vision deficiency called protanopia. To accomplish this task, the objective function of the fuzzy c-means is reformulated as to include only the cluster centers, and then it is minimized by the differential evolution. By using a standard technique, the original image is transformed to simulate the effect of the protanopia deficiency. Then, the above-mentioned clustering approach is separately applied to the original and the protanopia simulated images. By comparing the color clusters between these two cases, the colors in the original image are classified into two classes: (a) colors that must be corrected so that a protanope can easily distinguish them, and (b) colors that must remain intact. To this end, the colors belonging to the former class are adapted subject to the constraint that they must not be similar to the colors belonging to the latter class. Finally, the effectiveness of the proposed methodology is demonstrated through a number of experiments on color art paintings.