Abstract

This paper proposes the face identifying face characteristics for a person. As such, face recognition and detection algorithms have been the subject of hundreds of research papers, and algorithms have been designed for commercial use in digital cameras and phones. An Local gradient patterns (LGP) and binary histograms of oriented gradients (BHOG) algorithm is used to determine the location of the eyes, nose, and mouth of the face in the image. Based on these points, average human face proportions, image gradients, and edge detection of the face are then identified. This hybridization makes face and human detection robust to global illumination changes by local intensity changes by LGP and local pose changes by BHOG, which considerably improves detection performance.