Comparison of face recognition algorithms in the embedded systems

Today, biometry; it has become an indispensable part of human life. Every subject separating people from fingerprints to recognizing face to face is the field of biometric systems. These systems are used in many areas such as security, communication, marketing, defense and education. The concept of Internet of objects that came with Industry 4.0 brought about the need to define security and access to the devices related to the internet to open the embedded systems. Smart homes and wearable technologies have increased the speed of safety at the forefront. The camera is now installed on the embedded devices placed in smart homes, and the camera can be recognized by the camera. For example, when facing the television, it can open the channels according to personal preferences. Due to similar reasons, the number of smart homes that recognize the owner is increasing day by day. In this thesis, the face recognition algorithms presented by OpenCV library were examined by examining the operation of the embedded environment, and which algorithm was investigated.