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

机译:基于微分进化的模糊聚类法对人眼的颜色适应性研究:以数字化绘画为例

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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.
机译:道尔顿化过程是指图像的色彩适应性,以改善色盲观看者的感知。本文提出了一种改进的聚类方法,该方法适用于数字化艺术绘画的色彩适应,并涉及一种特殊的色觉缺陷,即泛盲现象。为了完成此任务,将模糊c均值的目标函数重新构造为仅包括聚类中心,然后通过差分演化将其最小化。通过使用标准技术,原始图像将被转换为模拟泛盲现象的效果。然后,将上述聚类方法分别应用于原始图像和普罗旺斯模拟图像。通过比较这两种情况下的色簇,原始图像中的颜色可分为两类:(a)必须校正的颜色,以便Protanope可以轻松地区分它们;以及(b)必须保持完整的颜色。为此,对属于前一类的颜色进行修改,以使其必须不与属于后一类的颜色相似。最后,通过对彩色艺术绘画的大量实验证明了所提出方法的有效性。

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