Young Researcher Paper Award 2021

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Vol. 32, No. 8(2), S&M2292

Print: ISSN 0914-4935
Online: ISSN 2435-0869
Sensors and Materials
is an international peer-reviewed open access journal to provide a forum for researchers working in multidisciplinary fields of sensing technology.
Sensors and Materials
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Automatic System for Detecting Student Attendance in College Classroom Based on Template Matching Method and Cellphone Storage Hanging Pocket

Weiping Lv, Lianyong Xiong, Jinshan Xie, and Cheng-Fu Yang

(Received March 29, 2022; Accepted May 18, 2022)

Keywords: template matching method, OpenCV, image segmentation, image recognition, binarization, contour detection

Because teachers in colleges and universities generally do not know the number of students in their classes, they spend considerable time monitoring student attendance, reducing the teaching time. In this study, we investigated a new method for effectively monitoring the attendance of students in classes of colleges and universities. When students enter a classroom at our campus, they must store their cellphones in a pouch containing multiple pockets that is hung from a wall of the classroom. These cellphone storage hanging pockets (abbreviated to cellphone pockets) have become a necessary tool for students to store cellphones and not only improve the efficiency of studying in the classroom, but are also convenient for teachers to check student attendance at the start of classes. We investigated a template matching method for efficiently finding the attendance of students using cellphone pockets. We used images of cellphone pockets as the input images for template matching to find the grids of the cellphone pockets with no cellphones. This enabled teachers to use the serial numbers of the cellphone pocket grids with no cellphones to identify the absent students.

Corresponding author: Weiping Lv, Cheng-Fu Yang

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