• Journal of the Institute of Electronics Engineers of Korea SC
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• v.48 no.5
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• pp.37-44
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• 2011

This paper proposes a confusion-line separating algorithm in a CIE Lab color space using color segmentation for protanopia and deuteranopia. Images are segmented into regions by grouping adjacent pixels with similar color information using the hue components of the images. To this end, the region growing method and the seed points used in this method are the pixels that correspond to peak points in hue histograms that went through a low pass filter. In order to establish a color vision deficiency (CVD) confusion line map, we established 512 virtual boxes in an RGB 3-D space so that boxes existing on the same confusion line can be easily identified. After that, we checked if segmented regions existed on the same confusion line and then performed color adjustment in an CIE Lab color space so that all adjacent regions exist on different confusion lines in order to provide the best color identification effect to people with CVDs.

• Journal of Korean Ophthalmic Optics Society
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• v.6 no.1
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• pp.139-144
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• 2001

In order to analyze of the color perception Farnsworth Test Panel D-15 in the CIELab color space coordinates, it was measured by the reflectance spectrum of the 380~780nm wavelength regions. The Test Panel D-15 was situated in the near origin point of higher the saturation in CIELab coordinates (a, b). Normal person perceived to the similar color for the color of small color difference, and color deficiency person depended on the confusing color line and the neutral point unconcerned with the color difference. In case of Ptotanopia, Deutrnopia, r-g defect, y-b defect with the color deficiency, the neutral points position (a,b) were each (2.12,1.02), (4.25,2.05), (2.51,0.25), (1.20,-1.10).