ct 18(17): e4

Research Article

Smart Attendance Management System Using Face Recognition

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  • @ARTICLE{10.4108/eai.13-7-2018.159713,
        author={Kaneez  Laila  Bhatti and Laraib  Mughal and Faheem Yar  Khuhawar and Sheeraz  Ahmed Memon},
        title={Smart Attendance Management System Using Face Recognition},
        journal={EAI Endorsed Transactions on Creative Technologies},
        volume={5},
        number={17},
        publisher={EAI},
        journal_a={CT},
        year={2018},
        month={10},
        keywords={Deep learning, python, Image Processing, Face_Recognition, Electron JS, HOG},
        doi={10.4108/eai.13-7-2018.159713}
    }
    
  • Kaneez Laila Bhatti
    Laraib Mughal
    Faheem Yar Khuhawar
    Sheeraz Ahmed Memon
    Year: 2018
    Smart Attendance Management System Using Face Recognition
    CT
    EAI
    DOI: 10.4108/eai.13-7-2018.159713
Kaneez Laila Bhatti1,*, Laraib Mughal1, Faheem Yar Khuhawar1, Sheeraz Ahmed Memon1
  • 1: Dept. of Telecommunication Engineering, MUET, Jamshoro, PK
*Contact email: Nbhatti11.nb@gmail.com

Abstract

To maintain the attendance record with day to day activities is a challenging task. The conventional method of calling name of each student is time consuming and there is always a chance of proxy attendance. The following system is based on face recognition to maintain the attendance record of students. The daily attendance of students is recorded subject wise which is stored already by the administrator. As the time for corresponding subject arrives the system automatically starts taking snaps and then apply face detection and recognition technique to the given image and the recognize students are marked as present and their attendance update with corresponding time and subject id. We have used deep learning techniques to develop this system, histogram of oriented gradient method is used to detect faces in images and deep learning method is used to compute and compare feature facial of students to recognize them. Our system is capable to identify multiple faces in real time.