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 Deep Learning- Based Surveillance System using Face Recognition

2020 ◽  
Vol 32 ◽  
pp. 03011
Author(s):  
Divya Kapil ◽  
Aishwarya Kamtam ◽  
Akhil Kedare ◽  
Smita Bharne
Keyword(s):  
Neural Network ◽  
Image Processing ◽  
Deep Learning ◽  
Face Recognition ◽  
Convolutional Neural Network ◽  
Surveillance System ◽  
Surveillance Systems ◽  
Learning Method ◽  
Security Systems ◽  
The Face

Surveillance systems are used for the monitoring the activities directly or indirectly. Most of the surveillance system uses the face recognition techniques to monitor the activities. This system builds the automated contemporary biometric surveillance system based on deep learning. The application of the system can be used in various ways. The face prints of the persons will be stored inside the database with relevant statistics and does the face recognition. When any unknown face is recognized then alarm will ring so one can alert the security systems and in addition actions will be taken. The system learns changes while detecting faces automatically using deep learning and gain correct accuracy in face recognition. A deep learning method including Convolutional Neural Network (CNN) is having great significance in the area of image processing. This system can be applicable to monitor the activities for the housing society premises.

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 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 Real-Time Attendance and Feedback System

2021 ◽  
pp. 1135-1139
Author(s):  
Piyush Manish Sonar ◽  
Aniket Nitin Chaudhari ◽  
Mehul Deepak Sethi ◽  
Tejaswini Sanjay Gadakh
Keyword(s):  
Face Recognition ◽  
Principal Component ◽  
Feedback System ◽  
Recognition System ◽  
Fingerprint Recognition ◽  
Student Attendance ◽  
Feedback Form ◽  
Face Recognition System ◽  
User Friendly ◽  
Facial Images

Face is the representation of one’s identity. Hence, we have proposed an automated student attendance system based on face recognition. Face recognition system is very useful in life applications especially for attendance system. In our proposed approach, firstly, video framing is performed by activating the camera through a user-friendly interface. In the pre-processing stage, scaling of the size of images is performed, if necessary, in order to prevent loss of information. In face recognition stage, enhanced local binary pattern (LBP) and principal component analysis (PCA) is applied correspondingly in order to extract the features from facial images. Another way of marking the attendance is fingerprint recognition. To mark the attendance students simply have to give the fingerprint impression in fingerprint scanner module. Finally, the attendance of the recognized student will be marked and saved in the excel file. The student who is not registered will also be able to register on the spot and notification will be given if students sign in more than once. Whenever seminar is completed then a link is sent on email. It includes the information in terms of feedback. When student fills the feedback form then analysis of overall session is done.

scholarly journals Face Detection & Recognition using Tensor Flow: A Review

2018 ◽  
Vol 18 ◽  
pp. 7381-7388
Author(s):  
Ishaan Chawla
Keyword(s):  
Social Media ◽  
Face Recognition ◽  
Access Control ◽  
Face Detection ◽  
Facial Recognition ◽  
Rapid Development ◽  
Standard Form ◽  
Surveillance Systems ◽  
Security Systems ◽  
Recognition Systems

Face recognition has become a popular topic of research recently due to increases in demand for security as well as the rapid development of mobile devices. There are many applications which face recognition can be applied to such as access control, identity verification, security systems, surveillance systems, and social media networks. Access control includes offices, computers, phones, ATMs, etc. Most of these forms currently do not use face recognition as the standard form of granting entry, but with advancing technologies in computers along with more refined algorithms, facial recognition is gaining some traction in replacing passwords and fingerprint scanners. Ever since the events of 9/11 there has been a more concerned emphasis on developing security systems to ensure the safety of innocent citizens. Namely in places such as airports and border crossings where identification verification is necessary, face recognition systems potentially have the ability to mitigate the risk and ultimately prevent future attacks from occurring. As for surveillance systems, the same point can be made if there are criminals on the loose. Surveillance cameras with face recognition abilities can aide in efforts of finding these individuals. Alternatively, these same surveillance systems can also help identify the whereabouts of missing persons, although this is dependent on robust facial recognition algorithms as well as a fully developed database of faces. And lastly, facial recognition has surfaced in social media applications on platforms such as Facebook which suggest users to tag friends who have been identified in pictures. It is clear that there are many applications the uses for facial recognition systems. In general, the steps to achieve this are the following: face detection, feature extraction, and lastly training a model.

scholarly journals RECOGNIZING FACES USING INDIVIDUAL EIGEN SUBSPACES TECHNIQUE WITH FUZZY RULES METHODOLOGY

2015 ◽  
pp. 164-169
Author(s):  
AISHWARYA P ◽  
KARNAN MARCUS
Keyword(s):  
Face Recognition ◽  
Principal Component ◽  
Rejection Rate ◽  
Security Systems ◽  
Major Objective ◽  
Face Representation ◽  
Face Images ◽  
The Face ◽  
Small Set ◽  
Effective Analysis

This paper proposes a new methodology of recognizing face using Individual Eigen Subspaces and it’s implemented in the field of Image Processing for Personnel verification or recognition. A major objective of this work is to develop a tool for face recognition, which can help in quicker and effective analysis of a face from the face set, thus reducing false acceptance rate and false rejection rate. Face recognition has been widely explored in the past years. A lot of techniques have been applied in various applications. Robustness and reliability have become more and more important for these applications especially in security systems. In this thesis, a variety of approaches for face recognition are reviewed first. These approaches are classified according to three basic tasks: face representation, face detection, and face identification. An implementation of the appearance-based face recognition method, the eigenface recognition approach, is reported. This method utilizes the idea of the principal component analysis and decomposes face images into a small set of characteristic feature images called eigenfaces. This proposed work is intended to develop, multiple face Eigen subspaces. With each one is corresponding to one known subject privately, rather than all individuals sharing one universal subspace as in the traditional eigenface method. Compared with the traditional single subspace face representation, the proposed method captures the extra personal difference to the most possible extent, which is crucial to distinguish between individuals, and on the other hand, it throws away the most intrapersonal difference and noise in the input.

scholarly journals Automatic Student Attendance System using Face Recognition

2020 ◽  
Vol 9 (3) ◽  
pp. 93-99
Keyword(s):  
Face Recognition ◽  
Recognition System ◽  
Automated Systems ◽  
Student Attendance ◽  
Face Recognition System ◽  
The Face ◽  
Face Detection And Recognition ◽  
Class Room ◽  
Current Systems ◽  
Detection And Recognition

The most common difficulty that every teacher faces in class room is to take the attendance of the students one by one in each and every class. For the time being many automated systems has been proposed for taking student attendance. In this paper, I introduced an automated student attendance system based on the use of unique techniques for face detection and recognition. This system automatically detects the student when he or she enters the classroom and recognizes that specific student and marks the student's attendance. This method also focuses on the specific features of different attributes such as the face, eye and nose of humans. In order to evaluate the performance of different face recognition system, different real-time situations are considered. This paper also suggests the technique for handling the technique such as spoofing and avoiding student proxy. This system helps track students compared to traditional or current systems and thereby saves time.

scholarly journals STUDENT ATTENDANCE SYSTEM BASED ON THE FACE RECOGNITION

2021 ◽  
Vol 6 (1) ◽  
Author(s):  
Harshit Agarwal ◽  
Govinda Verma ◽  
Lakshya Gupta
Keyword(s):  
Face Recognition ◽  
Recognition System ◽  
Graphical Interface ◽  
Student Attendance ◽  
Cascade Algorithm ◽  
Face Recognition System ◽  
The Face ◽  
Haar Cascade

Attendance system is very important in schools and colleges' The student attendance program has many problems such as it may not be accurate and critical to maintain. Therefore, an existing system that uses a face recognition system increases accuracy and also requires less time than other methods. There are many systems available such as face recognition using IoT, PIR sensors and so on. With face recognition, hardware devices are helpful. But the challenge is to keep all the nerves properly without getting hurt. After learning all the techniques and techniques we try to use the system with Haar Cascade Algorithm with the highest accuracy among them all. It can take pictures from 50- 70cm. We create a graphical interface that takes pictures, builds a database and trains the database with a single click. After seeing the face it will show the student's name and roll number. That information is stored on an automatic attendance sheet by time and date.

scholarly journals Attendance Management System using Face Recognition

2019 ◽  
Vol 8 (12) ◽  
pp. 1377-1381
Keyword(s):  
Face Recognition ◽  
Management System ◽  
Digital Data ◽  
Automated System ◽  
Security Systems ◽  
Human Machine Interaction ◽  
The Face ◽  
Commercial Applications ◽  
The Individual ◽  
Processing Techniques

Attendance management system is one of the tremendous challenges in any organization to reduce the malpractices by the individual. This paper aims to design automatic system for attendance using the face detection using LabVIEW (Vision Assistance Module) in order to replace the manual system and makes easier for the user to calculate the number of individuals and reduces the burden in taking attendance. Face recognition is one of the biometrics used in security systems, human machine interaction and image processing techniques [5]. This system is mostly helpful in security purpose and in commercial applications. It can be done by taking the image of the individual which is been captured by camera so that this image is converted into digital form. From this digital data the pattern of individuals is extracted so that everyone will have unique patterns. These patterns are stored in the database in excel format. The identification of the person is done by comparing the image captured through camera with the database images. Initially before starting the Attendance every individual is marked absent. Once the individual comes across the camera, the Automated system will extract the information by pre-processing the image with the help of Vision Assistance and extracts the patterns from the digital data. This data is compared with the stored patterns in database if the pattern matches with the database it automatically marks present

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