Intelligent Modification of Colors in Digitized Paintings for Enhancing the Visual Perception of Color-blind Viewers
Color vision deficiency (CVD) is quite common since 8%–12% of the male and 0.5% of the female European population seem to be color-blind to some extent. Therefore there is great research interest regarding the development of methods that modify digital color images in order to enhance the color perception by the impaired viewers. These methods are known as daltonization techniques. This paper describes a novel daltonization method that targets a specific type of color vision deficiency, namely protanopia. First we divide the whole set of pixels into a smaller group of clusters. Subsequently we split the clusters into two main categories: colors that protanopes (persons with protanopia) perceive in a similar way as the general population, and colors that protanopes perceive differently. The color clusters of the latter category are adapted in order to improve perception, while ensuring that the adapted colors do not conflict with colors in the first category. Our experiments include results of the implementation of the proposed method on digitized paintings, demonstrating the effectiveness of our algorithm.
KeywordsColor Vision Color Perception Color Cluster Digital Color Image Human Visual System Model
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