A Review of Numerous Facial Recognition Techniques in Image Processing

Recognizing faces in images is an emerging trend of research in image processing streams. There were various systems proposed in this stream. Human emotions and intentions are communicated more often by changes in one or two discrete facial features. Given a single image, the goal of face detection is to identify all image regions which contain a face regardless of its three-dimensional position, orientation, and lighting conditions. Such a problem is challenging because faces are no rigid and have a high degree of variability in size, shape, colour, and texture. Numerous techniques have been developed to detect faces in a single image, and the purpose of this paper is to categorize and evaluate these algorithms. We also discuss relevant issues such as data collection, evaluation metrics, and benchmarking. After analysing these algorithms and identifying their limitations, we conclude with several promising directions for future research.