Human Face Detection Technique using Haar-like Features

Research on biometrics has become most popular topic nowadays. Face is one of the most important biometric traits that plays a crucial role in our social association, passing on individuals’ identity. Face detection is very important and challenging topic in the field of biometric research. It is also an essential step of any face recognition system. The actual benefits of face-based recognition or identification are uniqueness and acceptance. Face recognition or identification also has distinct advantages over other biometric systems because of its non-contact process while capturing the facial image. Face images are captured from a distance without any touch to the person who is being identified and the entire identification process does not require interacting with the person. Face recognition is a method of identifying people throughout facial images and it has many practical applications in the area of biometrics, information security, access control, smart cards, law enforcement and surveillance system. Therefore, face detection/recognition is one of the most interesting and important topics in research field. The goal of this study is to explore the face detection system using conventional face detection techniques using Haar-like feature and Haar-cascade classifier using OpenCv library. An encouraging average accuracy of 95.16% was achieved in this experiment.