scholarly journals Attendance Management System using Face-Recognition

2021 ◽  
pp. 336-341
Author(s):  
Mrunal Aware ◽  
Prasad Labade ◽  
Manish Tambe ◽  
Aniket Jagtap ◽  
Chinmay Beldar
Keyword(s):  
Face Recognition ◽  
Management System ◽  
Educational Institutions ◽  
Face Identification ◽  
Roll Call ◽  
Student Attendance ◽  
Image Comparison ◽  
Sql Database ◽  
The Face ◽  
Computer Based

Nowadays Educational institutions are concerned about regularity of student attendance. Even in pandemic situation attendance is still a major issue in schools and colleges. Mainly there are two conventional methods of marking attendance which are calling out the roll call or by taking student sign on paper. They both were more time consuming and difficult. Hence, there is a requirement of computer-based student attendance management system which will assist the faculty for maintaining attendance record automatically. In this project we have implemented the automated attendance system using ‘TKINTER’ and ‘PYTHON’. We have projected our ideas to implement an “Automated Attendance System Based on Face Recognition”. The application includes face identification, which saves time as well as being purely softwere based it can be flagged as eco-friendly as it reduces the use of paper. This system also eliminates the chances of fake attendance because of the face being used as a biometric for authentication. Hence, this system can be implemented in a field where attendance plays an important role. The proposed system is designed in TKINTER platform supported with a script of PYTHON as well as SQL database. The algorithm used in the system is based on image comparison on the basis of the encoded values of the face from the image from database with the image recorded by the system in run time. The system has output in the form of excel sheet.

Algorithmic Analysis of Automatic Attendance System using Facial Recognition

2022 ◽  
Vol 14 (1) ◽  
pp. 0-0
Keyword(s):  
Face Recognition ◽  
Daily Life ◽  
Real Life ◽  
Student Attendance ◽  
Surveillance Camera ◽  
Daily Life Activities ◽  
The Face ◽  
Algorithmic Analysis ◽  
Human Faces ◽  
Face Biometrics

Attendance management can become a tedious task for teachers if it is performed manually.. This problem can be solved with the help of an automatic attendance management system. But validation is one of the main issues in the system. Generally, biometrics are used in the smart automatic attendance system. Managing attendance with the help of face recognition is one of the biometric methods with better efficiency as compared to others. Smart Attendance with the help of instant face recognition is a real-life solution that helps in handling daily life activities and maintaining a student attendance system. Face recognition-based attendance system uses face biometrics which is based on high resolution monitor video and other technologies to recognize the face of the student. In project, the system will be able to find and recognize human faces fast and accurately with the help of images or videos that will be captured through a surveillance camera. It will convert the frames of the video into images so that our system can easily search that image in the attendance database.

scholarly journals Dynamic & Intelligent Student Attendance Maintenance Based on Face Recognition

2020 ◽  
Vol 9 (5) ◽  
pp. 399-403
Keyword(s):  
Artificial Intelligence ◽  
Face Recognition ◽  
Face Detection ◽  
Student Attendance ◽  
Teachers And Students ◽  
The Face ◽  
Monitoring Camera ◽  
On Line

The proposed system generally results a solution to some of the problems which occurs in colleges and schools by providing a monitoring camera with the help of “Artificial Intelligence (AI)” . The main problem which can be occurred is wastage of time in taking the attendance manually or through any biometric sensors. The next problem which can be solved is to control the usage of electricity in classrooms when students are not in class. When the videos are getting recorded with the help of monitoring cameras, at the same time the head counting and face detection of the students present will also be done. When the strength of the class is zero ,the head counting also results to zero. The electricity can also be saved at the same time when people are not present in the classroom. The face recognition is the easiest process which can be done for marking the attendance, where the attendance is marked automatically. This process also helps to prevent the fake attendance. Face recognition and detection is generally based on line edge mapping to attain the identity of the student and also meets the wants of attendance in the universities and schools. The image of the student is to be captured and checked with the database simultaneously and marks the attendance of the particular student. The video gets recorded all the time and checks whether the student remains in class for the entire period.The attendance marking system with the help of technology is very essential for both the teachers and students.

scholarly journals Face Recognition Model Using Back Propagation

2018 ◽  
Vol 7 (3.34) ◽  
pp. 237
Author(s):  
R Aswini Priyanka ◽  
C Ashwitha ◽  
R Arun Chakravarthi ◽  
R Prakash
Keyword(s):  
Neural Network ◽  
Deep Learning ◽  
Face Recognition ◽  
Back Propagation ◽  
Back Propagation Neural Network ◽  
Face Identification ◽  
Identification System ◽  
Scientific World ◽  
The Face ◽  
Deep Learning Neural Network

In scientific world, Face recognition becomes an important research topic. The face identification system is an application capable of verifying a human face from a live videos or digital images. One of the best methods is to compare the particular facial attributes of a person with the images and its database. It is widely used in biometrics and security systems. Back in old days, face identification was a challenging concept. Because of the variations in viewpoint and facial expression, the deep learning neural network came into the technology stack it’s been very easy to detect and recognize the faces. The efficiency has increased dramatically. In this paper, ORL database is about the ten images of forty people helps to evaluate our methodology. We use the concept of Back Propagation Neural Network (BPNN) in deep learning model is to recognize the faces and increase the efficiency of the model compared to previously existing face recognition models.   

scholarly journals Attendance Management System using Google Facenet for Facial Recognition

2021 ◽  
Vol 9 (VI) ◽  
pp. 5029-5036
Author(s):  
Rakesh Duggempudi
Keyword(s):  
Image Processing ◽  
Face Recognition ◽  
Open Source ◽  
Management System ◽  
Facial Recognition ◽  
Cost Effective ◽  
Source Image ◽  
Student Attendance ◽  
Manual Work ◽  
View Update

Attendance management system is a required tool for attaining attendance in any habitat where attendance is essential. Yet, many of the available techniques consume time, are invasive and it demands manual work from the users. This research is directed at building a less invasive, cost effective and more efficient automated student attendance management system using face recognition that leverages on OpenCV functions for facial recognition. The system provides a GUI for marking attendance. It provides an interface for updating attendance using facial recognition libraries of OpenCV. The system stores attendance in a database which is maintained by the administrator. The administrator can view, update, and change the attendance of the students. The students can view and update their attendance. The system is developed on Open-Source image processing library and the interface is developed using Python Tkinter module. The Tkinter module is an open-source module by which we can develop GUI screens hence, it is not software dependent nor vendor hardware. The OpenCV module used for image processing is interfaced using python.

scholarly journals ASSAS: An automatic smart students attendance system based on normalized cross-correlation

2021 ◽  
Vol 10 (2) ◽  
pp. 732-741
Author(s):  
Ruaa H. Ali Al-Mallah ◽  
Dheyaa Alhelal ◽  
Razan Abdulhammed
Keyword(s):  
Image Processing ◽  
Face Recognition ◽  
Cross Correlation ◽  
Correlation Technique ◽  
Human Being ◽  
Roll Call ◽  
Student Attendance ◽  
Normalized Cross Correlation ◽  
Two Phases ◽  
Cross Correlation Technique

A smart student attendance system (SSAS) is presented in this paper. The system is divided into two phases: hardware and software. The Hardware phase is implemented based on Arduino's camera while the software phase is achieved by using image processing with face recognition depended on the cross-correlation technique. In comparison with traditional attendance systems, roll call, and sign-in sheet, the proposed system is faster and more reliable (because there is no action needed by a human being who by its nature makes mistakes). At the same time, it is cheaper when compared with other automatic attendance systems. The proposed system provides a faster, cheaper and reachable system for an automatic smart student attendance that monitors and generates attendance report automatically.

scholarly journals Face recognition attendance system using Local Binary Pattern (LBP)

2019 ◽  
Vol 8 (1) ◽  
pp. 239-245 ◽  
Author(s):  
Shamsul J. Elias ◽  
Shahirah Mohamed Hatim ◽  
Nur Anisah Hassan ◽  
Lily Marlia Abd Latif ◽  
R. Badlishah Ahmad ◽  
...  
Keyword(s):  
Image Processing ◽  
Face Recognition ◽  
Face Detection ◽  
Local Binary Pattern ◽  
Recognition System ◽  
Automated System ◽  
Student Attendance ◽  
Recognition Method ◽  
Face Recognition System ◽  
The Face

Attendance is important for university students. However, generic way of taking attendance in universities may include various problems. Hence, a face recognition system for attendance taking is one way to combat the problem. This paper will present an automated system that will automatically saves student’s attendance into the database using face recognition method. The paper will elaborate on student attendance system, image processing, face detection and face recognition. The face detection part will be done by using viola-jones algorithm method while the face recognition part will be carried on by using local binary pattern (LBP) method. The system will ensure that the attendance taking process will be faster and more accurate.

scholarly journals PENERAPAN EIGENFACE UNTUK COMPUTER BASED TEST (CBT) PENERIMAAN MAHASISWA BARU SEKOLAH TINGGI TEKNOLOGI ADISUTJIPTO

Compiler ◽  
2017 ◽  
Vol 6 (2) ◽  
Author(s):  
Haruno Sajati ◽  
Astika Ayuningtyas ◽  
Dwi Kholistyanto
Keyword(s):  
Face Recognition ◽  
Computer Technology ◽  
Digital Image ◽  
Facial Recognition ◽  
Security System ◽  
The Internet ◽  
Accuracy Rate ◽  
The Face ◽  
Computer Based ◽  
Or Applications

One of the development of computer technology is the availability of systems or applications that help human work everyday so that can be resolved quickly and correctly. The system, one of which is Computer Based Test (CBT). CBT is an application used for tests conducted using computers that are in the application there are some features of CBT security when working on the problem. CBT can use a stand-alone computer, a computer connected to a network or a computer connected to the internet. Facial recognition is a type of biometric application that can identify specific individuals in a digital image by analyzing and developing face patterns. In its implementation, CBT has a weakness in the security system that becomes the gap of CBT users to commit fraud, therefore required a good security system with the creation of CBT applications that use eigenface algorithm. It is necessary to have a security system that overcomes the problem that is required identification of face recognition of participants during the test so that cheating can be reduced. The results of the test using eigenface algorithm accuracy rate reached 82%, some things that affect the level of accuracy is, the intensity of light, facial position and the use of accessories on the face.

scholarly journals AUTOMATED ATTENDANCE SYSTEM WITH FACE RECOGNITION

2021 ◽  
Vol 5 (12) ◽  
Author(s):  
Akash Singh ◽  
Shreya Bhatt ◽  
Abhishek Gupta
Keyword(s):  
Face Recognition ◽  
Gradient Algorithm ◽  
Video Frame ◽  
Surveillance Systems ◽  
Student Attendance ◽  
Security Systems ◽  
Histogram Of Oriented Gradient ◽  
Federal Bureau Of Investigation ◽  
The Face ◽  
User Friendly

Face is the representation of one’s identity. So, we have prepared an automated student attendance system based on face recognition. This system is very useful in daily life applications especially in security and surveillance systems. The security systems on airport uses face recognition to identify suspects and the CBI (CentralBureau of Investigation) and FBI (Federal Bureau of Investigation) uses face recognition for criminal investigations. In our project also video framing is performed by accessing the camera through user friendly interface. The Face is detected and segmented from the video frame by using HOG (Histogram of Oriented Gradient) algorithm. In the first step or we can say in pre-processing stage, scaling of the size of the image is performed in order to prevent or reduce the loss of information. Then in next step, the ‘median filtering’ is applied to remove noise followed by the conversion of colour imageinto grayscale image. After that, CLAHE (Contrast Limited Adaptive Histogram Equation) is applied on the images to enhance the contrastof the image. Overall, we have created a program in python that take theimage from the database and make all the necessary conversions for recognition and then verifies the image inthe videos or in the real time by accessing the camera through user friendly interface. After the successful matchis found then it marks the name and time of the person in attendance sheet.

scholarly journals Digital Forensic Management System using Facial Recognition for Student's Participation and Registration on School Activities

2021 ◽  
Vol 14 ◽  
pp. 142-152
Author(s):  
C. Ratanaubol ◽  
P. Wannapiroon ◽  
P. Nilsook
Keyword(s):  
Face Recognition ◽  
Management System ◽  
The Other ◽  
Scanning System ◽  
Digital Imagery ◽  
Still Images ◽  
School Activities ◽  
Digital Forensic ◽  
Face Scanning ◽  
The Face

Face recognition technology is widely used in applications. But in some activities it may be too difficult to install the device and the registration boot. That requires both manpower and time, such as enrolling students to attend university activities. If you will use the face scanning system, one by one will waste a lot of time. The other method. It may be easy to falsify. Using digital imagery in student participation to solve problems by developing a system that can detect participants' faces in digital photographs obtained by taking still images and videos from several photographers. And collecting detailed pictures and videos throughout the event it is a digital proof to find the participants to verify their faces match with any student in the database. Who participate in that activity, the system will have Finding and comparing data of pre-recorded students' photographs and the algorithm would checks for duplicate data and records the activity in the database. Where users can specify category or activity name for later inspection

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