• SYED FAWAD HUSSAIN
• SYED IMTIYAZ HUSSAIN
• SANIYA SAJID
• MEHROZ ALI ANSARI
• SHUBHAKAR P

Attendance for the students is a key task in class. When done by calling roll numbers, it generally wastes the productive time of class. This proposed solution for the current problem is through automation of the attendance system using face recognition. The face is the primary identification for any human. This project describes the method of detecting and recognizing the face in real-time using Raspberry Pi. This project uses an efficient algorithm by using an open-source image processing framework known as Open CV. Our approach has five modules – Face Detection, Face Pre-processing, Face Training, Face Recognition and Attendance Database. The face database is collected to recognize the faces of the students. The system is initially trained with the student's faces which are collectively known as the student database. The system uses a user-friendly User Interface to maximize the user experience. This project can be used for many other applications. Raspberry Pi usage helps to minimize the cost of the product and the usability as it can be connected to any device to take attendance. This project uses a modified algorithm of Haar Cascades proposed by Viola-Jones for face detection, LBP histograms for face recognition and uses SQLite (a lite version of SQL in raspberry pi) along with MYSQL to update the database. The system will automatically update the student's presence in the class to the database. Then sends a message to guardians of absentees and also to the Head of the department. We have used an intelligent attendance system based on face recognition in this project. We have proposed to implement an attendance system for face recognization through these large applications are incorporated. The basic requirements for this system are Haar Cascades and LBP histogram for face recognization, which will first recognize the face of faculty followed by the students to identify the faces in real-time. Eigenvalues and Eigenvectors are affected both by light and exposer to the environment. We cannot ensure perfect light conditions in real-time. However, to overcome this problem, we have already used an LPF histogram. The system then compares the test image and the training image. Which are in the LiteSQL database then determines who is present and absent. If a student is absent a message will be automatically sent to the parent's phone number using the GSM module. We are installing the same intelligent face recognition system in the canteen area to monitor activities like the student is spending time in the canteen during class hours. The system will recognize the faces and will send an SMS to the respective HOD.

OpenCV is the result of these three components: the Haar cascade, LBPH recognizer, and Viola-Jones framework.

"FACE RECOGNITION BASED ATTENDANCE SYSTEM USING OPENCV (CNN)", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.8, Issue 6, page no.e215-e222, June-2021, Available :http://www.jetir.org/papers/JETIR2106590.pdf

"FACE RECOGNITION BASED ATTENDANCE SYSTEM USING OPENCV (CNN)", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.8, Issue 6, page no. ppe215-e222, June-2021, Available at : http://www.jetir.org/papers/JETIR2106590.pdf