Smart Attendance System

Abstract—We can make our Attendance Management System (AMS) intelligent by using a face-to-face recognition strategy. For that, we have to fix a CCTV camera at the classroom at any best point, which makes a person's picture at the fixed time and tests a face-to-face image. Traditionally, student attendance at the institutes is manually reported on the attendance sheets. It's not a productive operation, because it takes 5 or more minutes for attendance. Normally, the length of our class is 50 minutes, and every day we have more than 5 lessons. So, both courses spend more than 50 minutes, which is almost the same as our class time. For, solving this big issue we are proposed a novel automatic technique namely “Face Detection with OpenCV”. The system will be connected with our master database which includes the student's name, images, roll numbers, and time of attendance. This application mainly follows three steps. Firstly, it will take images. Secondly, compare them with the existing images which are storing in the master database. Thirdly, it will mark present all the matched images automatically on a spreadsheet and the remaining students will be absent from that class.

Introduction: A face-recognition attendance tracking device aims to ease the attendance process that takes a lot of time and the energies of the lecturer that can be used in teaching, which is a simple and easy way for students as well. The machine would collect the photographs of students present in the classroom and use a face-recognition model to mark attendance on the attendance sheet [1]. This method, made by an algorithm that only detects the student's face and then compares these recognized photographs from the master database, will be compiled at the time students enroll in a specific class or organization. Proposed Implementation will work in three separate sections, the first section to suit the photos of the students seated on the bench in that class. We need to make sure that the app has recorded all the photos of all the students presented. The second stage of the attendance monitoring device using facial recognition is the detection of faces that is the dynamic process in which the camera captures face images and, with the assistance of pre-feed data, the picture that was being captured will be recognized. The last step in this process is to upgrade the attendance list. The math photos will be classified as current and the remaining student market will be labeled as absent. Face recognition is the method of recognizing or confirming a human from any image that is collected either from an image capture system or from an actual image in a film. A machine doesn't have the high-level capability to understanding on its own. To detect and recognize faces, we must teach them using advanced concepts such as LBPH SVM and Bayesian are better classifiers [2]. The first step in this process is to find faces in the picture. To detect a face in a picture, it should be converted to grayscale for the first time because we don't need color. Now we're observing each pixel in the image and the pixels around it. Our task is to find out how dark the present pixel is relative to the pixels directly surrounding it. Then we want to draw an arrow indicating how the picture gets darker. By doing this, the effect is that we're turning the picture into a plain rep. Then we want to draw an arrow indicating how the picture gets darker. By doing this, the effect is that we're transforming the image into a simple representation of arrows called gradients. We then create a general pattern by extracting gradients from a lot of faces. Then compare it to the picture that we want to detect. This unique detection is called a histogram of gradients of HOG [3]. Using this application, the corresponding faculty will receive the presented and absent attendance without spending additional time to make a roll call. Our application can also be used by faculty, admin, and students. The admin will only update the details by encouraging newly enrolled students and the faculty control the record of the attendance and allowing students to track their attendance. Now, we are showing the specific users for specific work that can be done. The above are the duties of the professor. ➢ Launch the attendance session

➢ Take a look at the attendance

➢ Retrieve requests

➢ Regulation of the system

➢ Manual labeling of attendance

➢ Time

The above are the functionalities of the students

➢ View attendance at

Below are the roles of the administrator

➢ View attendance

➢ Retrieve queries

➢ Control over the system

➢ Update the database.