A skin-color extraction algorithm is proposed to detect human faces in color images with varying illumination condition and presence of complex background. The approach is based on both a Gaussian mixture model of human skincolor distribution and image segmentation using an automatic and adaptive multi-thresholding technique. Detected regions are then refined by morphological operations. Experimental results on images presenting a wide range of variations in lighting condition, face orientation, scale, pose, facial expression and background, demonstrate the efficiency of our skin-segmentation algorithm. Using additional information about facial features, our method becomes an efficient step in localizing candidate faces for a face detection system.