An Automated Attendance System Through Multiple Face Detection and Recognition Methods

被引：0
|
作者：
Meena, K. [1 ]
Swaminathan, J. N. [2 ]
Rajendiran, T. [3 ]
Sureshkumar, S. [2 ]
Imtiaz, N. Mohamed [4 ]
机构：
[1] Vel Tech Rangarajan Dr Sagunthala R&D Inst Sci &, Chennai, Tamil Nadu, India
[2] QIS Coll Engn & Technol, Ongole, India
[3] Saveetha Inst Med & Tech Sci, Saveetha Sch Engn, Chennai, Tamil Nadu, India
[4] GRT Inst Engn & Technol, Tiruttani, India
来源：
INNOVATIVE DATA COMMUNICATION TECHNOLOGIES AND APPLICATION, ICIDCA 2021 | 2022年 / 96卷
关键词：
Face recognition; OpenCV; Eigenfaces; Fisher face; Linear binary pattern histogram (LBPH); Haar cascade classifier;
D O I：
10.1007/978-981-16-7167-8_17
中图分类号：
TP39 [计算机的应用];
学科分类号：
081203 ; 0835 ;
摘要：
In this paper, a face detection-based attendance system is proposed and the comparison between different algorithms is evaluated. Haar cascade is used for face detection and for face recognition is implemented through LBPH, fisher face and eigenface. Real-time images are captured by using a camera and stored in the dataset. During prediction, the person's image is recognized and the database is updated with that person's id and the changes will get reflected in the excel sheet as well. The SMS is also sent to an appropriate number given by the student. The comparison is done among the three methods, and the best one is chosen. This paper also tells about preferring of OpenCV over MATLAB.
引用
收藏
页码：225 / 234
页数：10
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