• Journal of Digital Contents Society
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• v.19 no.7
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• pp.1397-1403
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• 2018

Today, modern people perceive skin care as part of their physical health care, and acne is a common skin disease problem that is found on the face. In this paper, an effective acne detection algorithm using CIE $L^*a^*b^*$ color space has been proposed. It is red when the pixel value of the component image $a^*$ is a positive number, so it is suitable for detecting acne in skin image. First, the skin image based on the RGB color space is subjected to light compensation through color balancing, and converted into a CIE $L^*a^*b^*$ color space. The extracted component image $a^*$ was normalized, and then the skin and acne area were estimated with the threshold values. Experimental results show that the proposed method detects acne more effectively than the conventional method based on brightness information, and the proposed method is robust against the reflected light source.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.41 no.2
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• pp.1-10
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• 2004

This paper proposes the method that design CLUT(color look-up table) simultaneously processing gamut mapping and color space conversion using only CLUT without complex computation. After CLUT is constructed using scanner gamut and printer gamut, the scanner gamut is extended to include original scanner gamut. This extended scanner gamut is used as input CIE $L^{*}$ $a^{*}$ $b^{*}$ values for CLUT. Then CMY values are computed by using gamut mapping. Input RGB image of scanner is converted into CIE $L^{*}$ $a^{*}$ $b^{*}$ by using regression function. CIE $L^{*}$ $a^{*}$ $b^{*}$ values of scanner are converted into CMY values without computation of additional gamut mapping using the proposed CLUT. In the experiments, the proposed method resulted in the similar color difference, but reduced the complexity computation than the direct computing method to process gamut mapping and color space conversion respectively.espectively.ively.

• Journal of Korea Multimedia Society
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• v.12 no.5
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• pp.633-643
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• 2009

We propose a color transfer method that used color contrast based templates to express the visual difference clearly between objects, while remaining the quality of the input image. Our algorithm employs colors of both the input image and template distributed on the $a^{\ast}b^{\ast}$chrominance plane of CIE $L^{\ast}a^{\ast}b^{\ast}$color space. The templates are made by considering the effect of color contrast and have the shape of either a line or a curve represented color distribution of the basic colors based gradation image. These tempates can be modeled on spline curves. We also generate simply new templates with the different basic colors by moving the control points of that curve. The color transfer method using the templates is done through a regressive analysis and color matching. We maintained color coherence of the input image by transforming similarly the color distribution of an input image to the one of templates.