Author(s): Neela Ashish Kumar, Swarnalatha P, Prudhvi Chowdary, Jai Krishna Naidu, Kailasa Sandeep Kumar

Email(s): neelaashishkumar@gmail.com , kailasasandeepkumar@gmail.com

DOI: 10.5958/2349-2988.2019.00016.0   

Address: Neela Ashish Kumar, Swarnalatha P, Prudhvi Chowdary, Jai Krishna Naidu, Kailasa Sandeep Kumar
Undergraduate Students, School of Computer Science and Engineering, Vellore Institute of Technology, Vellore
*Corresponding Author

Published In:   Volume - 11,      Issue - 2,     Year - 2019


ABSTRACT:
Nowadays, face recognition has become one of the key research regions in computer technology. Due to this scientists share a keen interest in this area. In this paper, we proposed an application of facial recognition in attendance marking system. The attendance marking system is a difficult process if it is done manually when there is a huge classroom with more number of students which is time-consuming. By using this facial recognition system we can avoid the issues of fake attendance, proxies and save time. In previous facial recognition attendance systems, there were some drawbacks such as intensity of light, head pose etc. The main research of this paper is to overcome those problems and provide the most accurate attendance marking system. This system which is primarily based face detection and recognition algorithms mechanically detect the student and mark the attendance when he enters the school room. The device architecture and algorithms utilized in each stage are defined on this paper. We used algorithms such as Viola-Jones for face detection, PCA for feature selection and SVM for classification. When as compared to conventional attendance marking system the proposed system saves time and effective way to maintain attendance and records of students.


Cite this article:
Neela Ashish Kumar, Swarnalatha P, Prudhvi Chowdary, Jai Krishna Naidu, Kailasa Sandeep Kumar. Smart Attendance Marking System using Facial Recognition. Research J. Science and Tech. 2019; 11(2):101-108. doi: 10.5958/2349-2988.2019.00016.0


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DOI: 10.5958/2349-2988 


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