Illumination-invariant color space and its application to skin-color detection

Color-based digital image processing (DIP) techniques have attracted much attention in many vision-based applications. However, due to color variations resulting from illumination changes, many color-based DIP techniques have yet to demonstrate a stable state of performance. Skin-color detection, which is one of the popular color-based DIP techniques, must overcome the illumination problems. We address the issue by presenting an illumination-invariant color space based on the image acquisition model that is determined by the Lambertian surface. Furthermore, we propose a method of skin-color detection based on the illumination-invariant color space. To evaluate the performance in terms of the illumination-invariant property, we perform a skin-color detection experiment. In the experiment, we compare the proposed method with the methods based on several color spaces. From the experiment, we achieve encouraging results, and our empirical experiments evidence both the effectiveness and the usefulness of the proposed method.