Face Recognition Based Attendance System
Problem Statement
Attendance is an important part of daily classroom evaluation. At the beginning and ending of
class, it is usually checked by the teacher, but it may appear that a teacher may miss someone or
some students answer multiple times. Face recognition-based attendance system is a problem of
recognizing face for taking attendance by using face recognition technology based on high-
definition monitor video and other information technology.
The concept of face recognition is to give a computer system the ability of finding and
recognizing human faces fast and precisely in images or videos. Numerous algorithms and
techniques have been developed for improving the performance of face recognition. Recently
Deep learning has been highly explored for computer vision applications. Human brain can
automatically and instantly detect and recognize multiple faces. But when it comes to computer,
it is very difficult to do all the challenging tasks on the level of human brain. The face
recognition is an integral part of biometrics. In biometrics, basic traits of human are matched to
the existing data. Facial features are extracted and implemented through algorithms, which are
efficient and some modifications are done to improve the existing algorithm models. Computers
that detect and recognize faces could be applied to a wide variety of practical applications
including criminal identification, security systems, identity verification etc. The face recognition
system generally involves two stages:
Face Detection – where the input image is searched to find any face, then image
processing
cleans up the facial image for easier recognition.
Face Recognition – where the detected and processed face is compared to the database of
known faces to decide who that person is.
Background
Many works related to Radio Frequency Identification (RFID) based Attendance Systems exist
in the literature. In RFID based system, students carry a RFID tag type ID card and they need to
place that on the card reader to record their attendance. RS232 is used to connect the system to
the computer and save the recorded attendance from the database. This system may give rise to
the problem of fraudulent access. Unauthorized person may make use of authorized ID card and
enter the organization. Fingerprint based Attendance System has a portable fingerprint device
which can be passed among the students to place their finger on the sensor during the lecture
time without the instructor’s intervention. This system guarantees a fool-proof method for
marking the attendance. The problem with this approach is that passing of the device during the
lecture time may distract the attention of the students.
Face detection is a basic technology of human-computer interaction. It can get information from
the faces in pictures or video. Face recognition technology analyses the face image to extract the
facial feature, and then identify specific target. The development of deep learning technology
further improves the accuracy of face recognition. Deep Learning CNNs (Convolutional Neural
Networks) have made significant breakthrough in image classification. The deep learning model
DeepID developed by the Computer Vision Research Group, have achieved a recognition rate of
99.15% on LFW database, which is higher than that of human eye with 97.52%
