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AutoAttend-Automated Attendance System using Facial Recognition

Metali Thareja, Mani Bhushan Jauhari, Dr Atul Kumar

Abstract


Many attendance management systems that existed back in the day lacked efficiency and information sharing. The different prevalent methods to obtain person's presence like roll call and finger biometrics for attendance are time-consuming and require long processing time. Automated Attendance system uses face biostatics accompanied by the techniques of image processing and machine learning algorithms to recognize students. Face recognition technology complementary to Image Processing is gradually evolving to a universal biometric solution since it does not require any virtual effort from the user as compared to other biometric options. The main objective of this paper is to analyse the different approaches proposed by various authors and develop a real-time attendance monitoring system that overcomes the shortcomings of existing methods. The approaches vary in terms of input methods used, type of data processing employed and the controllers used in the implementation of the systems. The Proposed System is provided with snaps on which face detection and recognition technique is applied. After faces are detected, they are recognized by matching them with existing database, system updates the attendance for all recognized members with their respective id. An excel sheet is generated for the attendance record. This paper highlights comparison of different approaches while proposing an innovative smart system that can be user-friendly and provide convenience to various institutions.

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References


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