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.
