  In Computer Vision, colour-based spatial techniquesoften assume a static skin
colour model. However, skin colour perceived by a camera can change when
lighting changes. In common real environment multiple light sources impinge on
the skin. Moreover, detection techniques may vary when the image under study is
taken under different lighting condition than the one that was earlier under
consideration. Therefore, for robust skin pixel detection, a dynamic skin
colour model that can cope with the changes must be employed. This paper shows
that skin pixel detection in a digital colour image can be significantly
improved by employing automated colour space switching methods. In the root of
the switching technique which is employed in this study, lies the statistical
mean of value of the skin pixels in the image which in turn has been derived
from the Value, measures as a third component of the HSV. The study is based on
experimentations on a set of images where capture time conditions varying from
highly illuminated to almost dark.
