Real-Time Attendance Recording System using Face
Recognition Technology
Mustafa Bohra, Mohammed Raza, Mustafa Attarwala,
Mufaddal Habibi , Mohit Attri , Hanik Mazen
Abstract - The management of the
attendance can be a great burden on the
teachers if it is done by hand. To resolve this
problem, a smart and auto attendance
management system is being utilized. But
authentication is an important issue in this
system. The smart attendance system is
generally executed with the help of
biometrics and by python in-built libraries.
Face recognition is one of the biometric
methods to improve this system. Being a
prime feature of biometric verification,
facial recognition is being used enormously
in several such applications, like video
monitoring and smart CCTV footage
system and Vehicle Identify & Counting
System, By utilizing this new programming
framework, the problem of proxies and
students being marked present even though
they are not physically present can easily be
solved. The main implementation steps used
in this type of system are face detection and
recognizing the detected face. This paper
proposes a model for implementing an
automated attendance management system
for students of a class by making use of face
recognition technique, by using Face-
Recognition in-built modules and OpenCV,
Facial recognition systems attempt to
identify a human face, which is three-
dimensional and changes in appearance with
lighting and facial expression, based on its
two-dimensional image After these, the
connection of recognized faces ought to be
conceivable by comparing with the database
containing student's faces. This model will
be a successful technique to manage the
attendance and records of students.
I. INTRODUCTION
To verify the student attendance record, the
personnel staff ought to have an appropriate
system for approving and maintaining the
attendance record consistently.
The following document is a report on the
mini Course project on Real-Time
Attendance Recording systems using Face
Recognition Technology It involved
building a system for face detection and face
recognition using several classifiers
available in the open computer vision library
(OpenCV). Face recognition is a non-
invasive identification system and faster
than other systems since multiple faces can
be analyzed at the same time. The difference
between face detection and identification is,
face detection is to identify a face from an
image and locate the face. Face recognition
is making the decision “ Whose face is this
“, using an image database collection. In this
project, both are accomplished using
different techniques and are described
below. The report begins with a brief history
of face recognition. This is followed by the
explanation of HAAR-cascades, Eigen-face,
Fisher-face, and Local binary pattern
histogram (LBPH) algorithms. A discussion
regarding the challenges and the resolutions
