Face detection using the 3×3 block rank patterns of gradient magnitude images and a geometrical face model
Kang-Seo Park, Rae‐Hong Park, Young‐Gon Kim · 2011
Face detection is required prior to various face-related applications. The objective of face detection is to determine whether or not there are any faces in an image and, if any, the location of each face is shown. Face detection in a natural scene image is challenging due to large variability of face appearances. This paper proposes a face detection algorithm using the 3×3 block rank patterns of gradient magnitude images and a geometrical face model. The 3×3 block rank patterns are used to roughly classify whether the detected face candidate region contains a face or not. Finally, the face, if any, is detected by using a geometrical face model. Experimental results show that the proposed face detection algorithm is insensitive to illumination in natural scene images.