Towards Automatic Skin Tone Classification in Facial Images

In this paper, we address the problem of skin tone classification in facial images, which has applications in various domains: visagisme, soft biometry and surveillance systems. We propose four skin tone classification algorithms and analyze their performance using different color spaces. The first two methods rely directly on pixel values, while the latter two divide the image into cells and classify the skin tone based on the color histograms of these cells. The proposed solutions were trained and evaluated on images from four publicly available databases and on images captured in our laboratory. The best accuracy (87.06%) is obtained using cell histograms of the Lab color space and support vector machine classifier.

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