Tezislər / Theses



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BHOS Tezisler 2022 17x24sm

THE 3
rd
 INTERNATIONAL SCIENTIFIC CONFERENCES OF STUDENTS AND YOUNG RESEARCHERS 
dedicated to the 99
th
anniversary of the National Leader of Azerbaijan Heydar Aliyev
166
FACE RECOGNITION AND ATTENDANCE CHECKING 
Ilgar Mammadov 
Baku Higher Oil School 
Baku, Azerbaijan 
ilgar.mammadov.std@bhos.edu.az 
Supervisor: PhD, Associate Professor Leyla Muradkhanli 
Keywords: 
face recognition, attendance checking system, deep convolutional neural 
network, support vector machine 
Abstract 
This thesis investigates an attendance checking system that is based on 
face recognition algorithm. In this paper the theory behind the face recognition 
is explained, its usage in attendance checking process is analyzed, and the 
required software is explained. 
Introduction 
In the modern world, face recognition system is used extensively and 
solves many time-requiring problems rapidly. This system can be applied to 
attendance checking process as well.
Even though some modernized methods are used for that purpose, they 
also have some disadvantages. For example, in many places, attendance is 
recognized by fingerprint sensors. However, the main inefficiency is the time 
required for the attendees to wait in the queue. Additionally, one global 
problem today is the pandemic illnesses and pressing finger to the same sensor 
one-by-one increases the risk.
Instead, broad usage of face-recognition systems for taking the attendance 
can lead to the more efficient time-control and reduced risk of infectious 
diseases.
Face recognition algorithm 
The steps that are performed by the algorithm are as follows: 
1. Capture an image with a camera 
2. Convert the image to grayscale 
Compare the intensities of pixels and generate arrows (gradients) to 
differentiate darker pixels. The result will be 
histogram of oriented gradients 
image (HOG) (Figure 1.)
:
Figure 1. 
Histogram of oriented gradients image (HOG)



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