期刊名称：Signal & Image Processing : An International Journal (SIPIJ)
印刷版ISSN：2229-3922
电子版ISSN：0976-710X
出版年度：2013
卷号：4
期号：5
页码：27
出版社：Academy & Industry Research Collaboration Center (AIRCC)
摘要：Face detection locates faces prior to various face-related applications. The objective of face detection is todetermine whether or not there are any faces in an image and, if any, the location of each face is detected.Face detection in real images is challenging due to large variability of illumination and face appearances.This paper proposes a face detection algorithm using the 3×3 block rank patterns of gradient magnitudeimages and a geometrical face model. First, the illumination-corrected image of the face region is obtainedusing the brightness plane that is produced using the locally minimum brightness of each block. Next, theillumination-corrected image is histogram equalized, the face region is divided into nine (3×3) blocks, andtwo directional (horizontal and vertical) gradient magnitude images are computed, from which the 3×3block rank patterns are obtained. For face detection, using the FERET and GT databases three types of the3×3 block rank patterns are a priori determined as templates based on the distribution of the sum of thegradient magnitudes of each block in the face candidate region that is also composed of nine (3×3) blocks.The 3×3 block rank patterns roughly classify whether the detected face candidate region contains a face ornot. Finally, facial features are detected and used to validate the face model. The face candidate isvalidated as a face if it is matched with the geometrical face model. The proposed algorithm is tested on theCaltech database images and real images. Experimental results with a number of test images show theeffectiveness of the proposed algorithm.
