Study of Face Detection Algorithms

With innovation in network technologies, industrial dependency on network technology is increasing day by day. Due to which network information security issues are increasing. With development of industrialization, the use of sensors has become extensive. Sensors perceive some signals and convert those signals into an electrical signal and records it. With use of conversion circuit, it transfers electrical signal into a digital form or other display form that is conducive to observation. Based on original function, which is combined with computer technology, it now integrates to store data, communicate data, process data and display better information. In early days finger and palm lines used to scan to recognise person. But this method has certain limitations. This research paper proposes new computer-based algorithms from face detection technology. Face detection technology is mainly introduced from the OpenCV method. By using contrast experiment, the detection rates under the three different requirements of side face detection, occlusion detection and facial exaggerated expression are compared. It is found that accuracy of each method is improved. The advantages and disadvantages of the algorithm verifies the effectiveness of the method. Artificial neural networks are the most popular method in image recognition. The algorithms perform three main tasks. It detects faces in real-time through camera, video or through images. It then calculates mathematical model of a face and compares models with database or training sets.