Face detection is a preprocessing step for facial recognition systems. The goal is to localize faces in digital images and video in real-time. Skin is an important element for detecting images containing skin or skin-like regions, as skin covers most of the face and varies less in color than brightness between people. The researchers used a mathematical model of skin color represented in three color spaces (rg, HSB, and YCbCr) generated from face images. Skin was modeled using mean and covariance characteristics of chromaticity from training images. Face detection was performed by calculating the probability that each pixel belonged to the skin distribution model in the color spaces. Experiments were conducted on over 3,000 face images from seven databases. Accuracy needs improvement