Modification of indistinguishable colors based on personal characteristic model for people with color defective vision

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Compared to people with normal color vision, people with color vision deficiency(CVD) have difficulty in distinguishing between certain combinations of colors. To address this problem, we modify saturation components of the original image to preserve visual detail when perceived by people with CVD. The proposed method can automatically construct a transformation to maintain details for people with CVD while preserving naturalness for normal viewers. In addition, high-speed processing of re-coloring is achieved by clustering based on color quantization using the median cut algorithm. On the other hand, to classify type of vision disability, we implemented the farnsworth-munsell D-15 test to a mobile device with android OS. Finally, in order to show the effectiveness of the proposed system, we performed evaluational experiments. In addition, we proposed automatic image segmentation by using the maximum distance algorithm for an image which has indistinguishable colors.