Identity Authentication System Using Face Recognition Techniques in Human-computer Interaction

Abstract

Automatic and separately identifying human faces is one of the most challenging issues at present. Although in a little light through the video monitoring cameras, recognizing people's faces is abit default. Our proposed system handles thirty-five pixels better at minimum low resolution to detect human faces in different angles and different face detection. In our system, we use the LBPH algorithm to recognize people's faces in low light and at low resolutions. Here we will take 20 to 30 pictures of a human and create his dataset from different angles. Next, using that data seat, we will train the data in the OpenCV library of Python. In the case of each data set of people will be taken from different angles, then all related information will be stored in a specific database. Each human's data set will be stored in a specific database if each input is inputted. Our system can display all its information in just 2 seconds by detecting a human face. To recognize people's faces, they will show all the data from the database and using all this information we will develop a security system or create a report system.