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Intelligent Modification of Colors in Digitized Paintings for Enhancing the Visual Perception of Color-blind Viewers

机译:智能修改数字绘画中的颜色以增强色盲查看者的视觉感知

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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.
机译:色觉不足(CVD)非常普遍,因为欧洲的男性人口中有8%-12%,女性中有0.5%似乎在一定程度上存在色盲。因此,对于改进数字彩色图像以增强受损的观看者的色彩感知的方法的开发具有极大的研究兴趣。这些方法被称为道尔顿化技术。本文介绍了一种针对特定类型的色觉不足(即黑盲)的新型道尔顿化方法。首先,我们将整个像素集划分为较小的群集组。随后,我们将聚类分为两大类:普塔诺普斯(具有普罗旺斯的人)感知的颜色与普通人群的感知方式相似,以及普塔诺普斯的感知方式不同。调整后一类的颜色簇以改善感知,同时确保所适配的颜色与第一类中的颜色不冲突。我们的实验包括在数字化绘画上实现该方法的结果,证明了我们算法的有效性。

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