Face Recognition Based Attendance System Using Opencv (CNN)

Attendance is important for each and every students in schools and colleges. This paper deals with the process of taking the attendance with use camera and automating the attendance process that will mark the attendance for the students in easy and simple manner without wasting of time and reduce Statistical process. This proposed system uses face detection for identification of face from objects and face recognition for matching of faces from stored database images (authentication) and provide attendance according to the matched face. To attain this face detection and recognition, we use viola-Jones algorithm (Haar's Cascade) for face detection and linear binary pattern histograms for face authentication using python and importing the OPENCV framework to python IDE. This system updates attendance of the student and sends message to the Head of the Department.

2023

Face recognition technology has gained substantial attention owing to its diverse applications. One of the applications includes a face recognition-based attendance system which stands out the most among all the existing attendance systems because of its heightened security and time-saving capabilities. A face recognition system is the process of recognizing an individual based only on their facial traits. This paper proposes a real-time face recognition attendance system that validates the real-time monitoring of the process. OpenCV has been used to create a Haar cascade classifier, which is used to recognize faces. The face recognition algorithm Local Binary Pattern Histogram (LBPH) has been chosen in this system due to its robustness and better applicability in the real world. This proposed method can identify the faces of individuals effectively from various angles. The results prove the validation of the work through the monitoring of students' attendance.

International Journal for Research in Applied Science & Engineering Technology (IJRASET), 2022

In the recent time automated face recognition has become a trend and has been developed very much , this is mainly due to two reasons; first it is due to availability of modern technologies and second is due to the ability to save time using face recognition in the process of taking attendance of students. Its usage will grow vast in the future as it saves a lot of time. It consumes a lot of time to take attendance manually and few might also fake the attendance, in order to prevent time consumption and avoid faking the attendance face recognition is used to identify the person present in the class and mark his attendance , this is done with the help of image or video frame. We proposed an automatic attendance management system using machine learning techniques such as CNN algorithm. The face detection and recognition will automatically detect the students in the classroom and mark the attendance by recognizing the person.. The faculty has access to add the student details such as name, USN, phone number, email-id. Then the image is captured through a high definition camera during the class hours. When the lecturing is going on faces of students are detected, segmented and stored for verification with database using the Convolutional Neural Networks (CNN) algorithm of machine learning technique

International Journal of Scientific Research in Computer Science, Engineering and Information Technology, 2023

Face detection and recognition systems work by detecting faces present in an image or in a video frame and identifying the person in the image. In this work, we are interested in face detection to achieve an automatic attendance system. This work is implemented using Python and can be operated from any standalone device. This automated system stores the attendance records of students/employees with proper timestamps in the local Secondary Memory. All these records are stored date-wise. The implementation of an Automated Facial Recognition based Attendance System can help in identifying and verifying a person’s identity from a digital source in real-time. Accurate attendance records are very important for classroom evaluation in schools and colleges. It also helps to keep track of the attendance of the employees in different organizations. The traditional system of manual attendance tracking in institutes can result in errors and missed or duplicated entries. The adoption of the Face Recognition-based attendance system could help eliminate these problems and shortcomings of the classical manual attendance system. The proposed work is tested with different persons with different age groups and genders in real time. The system successfully identifies the proper persons with significant accuracy and records their attendance.

International Journal for Research in Applied Science and Engineering Technology IJRASET, 2020

Face recognition Technology is being appealing field in recent years. Taking attendance is a real-world task, which needs a creative solution to reduce time, efforts and resources. Face recognition Attendance is a technique to detect and recognize the students' or employees' face for marking their attendance by using unique face features extracted from the images captured. In proposed face recognition project, a raspberry PI based system will be able to detect and recognize human faces in a quick and accurate way via images or videos that are being captured through a Camera. It detects the faces within the image and compares it with the listed faces in the database. On recognition of a registered face on the captured image assortments, the attendance of that student is marked present otherwise absent. The system is developed on Open Source image processing library hence; it is not hardware nor software dependent. Many algorithms are used to ameliorate the performance of the system but the concept to be implemented here is Eigen matrix concept (Eigen Faces). It is used to convert the images into the matrix, based on the features of the images, to easily recognize the faces of the students, so that the attendance database can be easily updated. I. INTRODUCTION Presently, attendance management is important task in every educational organization. Managing students' attendance during lecture period is time consuming task. The most of the institutions uses pen-paper based approach and some have adopted automated methods such as fingerprint biometric techniques and RFID based attendance System. However, these techniques make students to wait in a queue that depletes time and it is intrusive. Some institutions still use manual attendance approach in which a subject teachers call out the students' name and mark the attendance manually. This approach may be considered as a time-consuming or sometimes it happens for the teacher to miss someone to mark present or students may answer multiple times to make proxy attendance of their friends. So, the problem of accuracy and reliability arise when we think about the traditional process of taking attendance in the classroom. Face recognition technology is one of the least intrusive and fastest growing technology. Face recognition based attendance is an approach to automatically mark the presence or the absence of the student in the classroom by recognizing their faces. It can also be implemented in the exam sessions to ensure the presence of the real student who has registered for exam. It works by identification of humans using the most unique characteristics of their faces via images captured through camera, so it becomes highly reliable for the machine to mark the presence of all the students available within the room. The concept of this paper is aimed towards developing a less intrusive, economical and more efficient automated student attendance managing system using face recognition. II. EXISTING METHODS Some systems exist in automated attendance technique. However, only a few are enforced implementing a less intrusive approach. Some existing systems include Finger print based attendance, Iris based attendance and RFID based attendance. In this research, my focus is on face recognition and a cost effective architecture for its implementation. Face recognition based attendance system with raspberry pi 3A+ using Eigen faces algorithm has been proposed. In the work, a camera is placed at top position of the class that cover whole class which is interfaced with a raspberry pi 3A+ module for capturing students entering the class. The images are stored in the raspberry pi 3A+. The raspberry pi 3A+ module is used to achieve high speed of operation.

GRD Journals , 2021

The conventional attendance system consists of registers marked by teachers which leads to human error and a lot of maintenance. Time consumption is an important point of concern in this system. We have thought of revolutionize it using available digital tools in the modern era i.e. FACE RECOGNITION. Our project will ensure more precision and negligible manual work. The project is revolutionized in order to overcome the problems of conventional system. Face recognition and then marking the attendance is our project all about. The database of all the students in the class is stored in a folder and when the face of the individual student matches with one of the faces stored image, attendance is marked else the face is ignored and attendance not marked. In our project, face recognition (Machine Learning) technology is used .Inside this Histogram of Oriented Gradient for face detection and SVM Classifier for name recognition is used. The model has an accuracy of 99.38% on the Labelled Faces in the Wild benchmark.[2].

2019

To identify a person in real environment, face is the essential recognizable proof of any human in daily lives. Image processing based attendance system is the simplest way for keeping attendance in many organizations. Traditional way of enrolling one by one on paper takes some time to record attendance and also it is insecure. For each lecture this is inefficient. To avoid these losses, automatic process is intended to use which is processing with image. In this novel approach, biometric identification system of face is used to identify daily attendance and Raspberry Pi is applied as manipulating processor. In the proposed system, Eigenface algorithm is used because Eigen-face algorithm is less wastage of time and more effective than other algorithms. This system is implemented by using Python with OpenCV library. With the help of this system, time will be saved and it is great convenient to record the attendance at any time throughout the day.

Pure science and Technology Applications (SCUG-PSTA-2022), 2022

One of the most beneficial uses of image processing is face recognition, which is essential in today's technology environment. Particularly when it comes to tracking student attendance, the identification of a human face is a popular issue in the authentication sector. A face recognition attendance system is a technique for identifying pupils based on high-definition surveillance and other computer technologies that employ face biostatistics. The purpose of creating this system is to electronically replace the conventional procedure of recording attendance by calling names and maintaining paper records. The existing procedures for taking attendance are cumbersome and time-consuming. Our goal and ambition for this article is to use the OpenCV library to develop an attendance management system that can identify faces and store them in a database so that colleges, businesses, and other institutions may use it to track attendance. This research will use a combination method of using Open CV and HOG library detecting the face in boundary box with accuracy %99.38. Adding more, it has been proposing new idea of using these techniques in all halls and labs in any educational institutes in recording the student's attendance precisely.

International Journal for Research in Applied Science & Engineering Technology (IJRASET), 2022

Existing system of attendance system is a manual entry of the students attendance. Handwritten registers will be used to keep track of attendance. The user’s record will need to be maintained, which will take more time. The human effort is more here. The face is the most distinguishing feature of any human

In this paper, we propose a system that takes the attendance of students in the lecture. This system takes the attendance automatically using face recognition. However, it is difficult to estimate the attendance exactly using each result of face recognition independently because the face detection rate is not sufficiently high. In our paper, we propose a method for estimating the attendance exactly using all the results of face recognition obtained by continuous observation. Continuous observation improves the performance for the estimation of the attendance. We constructed the attendance system based on face recognition, and applied the system to classroom lecture. In our system, we are using raspberry pi. we use OpenCv library which is installed in pi for face detection and recognition. The camera is connected to raspberry pi and student database is stored in the pi. With the help of this system time will reduce and attendance will be marked.