The Smart Attendance Monitoring System
M. Sasi Chandra1, Radhika Baskar2
1M. Sasi Chandra, UG Scholar, Department of Electronics and Communication Engineering, Saveetha School of Engineering, Saveetha Institute of Medical and Technical Sciences, Chennai (Tamil Nadu), India.
2Dr. Radhika Baskar, Associate Professor, Department of Electronics and Communication Engineering, Saveetha School of Engineering, Saveetha Institute of Medical and Technical Sciences, Chennai (Tamil Nadu), India.
Manuscript received on 08 September 2019 | Revised Manuscript received on 17 September 2019 | Manuscript Published on 11 October 2019 | PP: 62-66 | Volume-8 Issue-11S September 2019 | Retrieval Number: K101309811S19/2019©BEIESP | DOI: 10.35940/ijitee.K1013.09811S19
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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: As an important part of class teaching, attendance plays a key role in the evaluation of teaching. At the beginning and end of class, it is usually checked by the teacher, but it may appear that miss someone or some students answer multiple times. To overcome this issue, the latest technology is used to detect the faces and recognize the faces using python programming. Face Detection is the best significant topics of computer technology in machine learning application. This technology has been available for some years now and is being used all over the world. In this paper, capturing the images of students from the database and faces are detected by the algorithm and then it is acknowledging with the database and at last, the attendance is recorded. For detecting faces Viola-Jones facial identification algorithm is used and for recognizing the faces from the databases(LBPH) Local Binary Patterns Histograms technique is used.
Keywords: Python, Viola-Jones Algorithm, Local Binary Patterns Histograms (LBPH), Machine Learning.
Scope of the Article: Smart Spaces