Skin Color Detection through Estimation and Conversion of Illuminant Color Under Various Illuminations

Abstract

Skin color provides a useful cue for detecting faces and reproducing preferred colors. However, skin color detection based on just a static model often decreases the detection rate, as skin color in an image captured by a camera undergoes variations as the illumination changes. Thus, to enhance skin color detection using a static model, the color of an estimated illuminant from images captured under various illumination conditions is converted to that of a canonical illuminant. First, the illuminant color is estimated from the pixels in the sclera region of the eyes, then converted to a canonical color for robust skin color detection. Experimental results show that the proposed skin color detection method increases the detection rate, especially for images taken with a low or high correlated color temperature of illumination.