Low Light Face Detection System

Abstract

Detection of faces from low light image is challenging. Such images often suffer from poor contrast, poor intensity, and high noise make it challenging to gather information and identify people or objects. The proposed method uses a deep learning-based approach to enhance the images by capturing multiple exposures and combining them to generate a high-quality image. Max-margin object detection (MMOD) human face detector, a face detection algorithm is used to identify and enhance the faces in the images. MMOD algorithm is a deep learning-based object detection approach which accurately detects human faces in images. By identifying and enhancing the faces in the images, they are made more visible and recognizable, even in low light conditions. The experimental results of this proposed approach demonstrate its effectiveness in enhancing face visibility and raising the quality of low-light images. This method has practical applications in areas such as security surveillance, where capturing high-quality images under low light conditions is critical.