Attendance Maintaining and Monitoring using Face Recognition
C. Kalpana1, S.Hemavathi2, K.Geerthana3, T.Dhakshayini4
1C. Kalpana*, Computer Science and Engineering, Sri Manakula Vinayagar Engineering College, Puducherry, India.
2S.Hemavathi, Computer Science and Engineering, Sri Manakula Vinayagar Engineering College, Puducherry, India.
3K.Geerthana, Computer Science and Engineering, Sri Manakula Vinayagar Engineering College, Puducherry, India.
4T.Dhakshayini, Computer Science and Engineering, Sri Manakula Vinayagar Engineering College, Puducherry, India.
Manuscript received on March 15, 2020. | Revised Manuscript received on March 30, 2020. | Manuscript published on April 10, 2020. | PP: 1823-1828 | Volume-9 Issue-6, April 2020. | Retrieval Number: F3566049620/2020©BEIESP | DOI: 10.35940/ijitee.F3566.049620
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: Technology has been playing a vital role in this world, where the work and the work place become digitalized. The paper reviews on monitoring the attendance using image processing, which involves face detection, labeling the detected face, training a classifier based on labeled dataset, and face recognition. Former methods on monitoring the attendance includes signing the attendance registry, fingerprint detection and barcode scanning where delinquency may occur. To prevail over and to take the technology to subsequent level image processing has been incorporated. Proposed system employs, capturing of the face in various dimensions, labeling of the captured images that is stored in the database for training and testing phase. Using the gathered data the machine is trained to recognize the face to provide access to the employees or students in the organization. The final phase is to take the attendance and maintain the record on attending hours using face recognition technique in which the input image of the employees or students is given.
Keywords: Attendance, Boolean Value, Classification, Face Detection, Regression.
Scope of the Article: Pattern Recognition