Smart Attendance Notification System using SMTP with Face Recognition
YB. PruthviRaj Goud1, S. Sravan Reddy2, K. Praveen Kumar3
1B. PruthviRaj Goud*, Assistant Professor in Dept of Information Technology, Anurag Group of Institutions, Hyderabad, India.
2S. Sravan Reddy, Assistant Professor in Dept of Information Technology, Anurag Group of Institutions, Hyderabad, India.
3K. Praveen Kumar, Assistant Professor in Dept of Information Technology, Anurag Group of Institutions, Hyderabad, India
Manuscript received on February 10, 2020. | Revised Manuscript received on February 23, 2020. | Manuscript published on March 10, 2020. | PP: 337-342 | Volume-9 Issue-5, March 2020. | Retrieval Number: D1506029420/2020©BEIESP | DOI: 10.35940/ijitee.D1506.039520
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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: Till today attendance marking is manual event for many educational bodies. It is a mandatory, common and important activity in day to day life of a faculty member. Manual attendances maintaining is bit difficult process, time consuming effort while doing analysis or report generations on it. Few automated systems are developed to overcome those complexities. Still there are so many drawbacks like cost effective, fake generation, accuracy. To overcome these initiations, there is a need of innovative a smart and automated attendance system. This paper exactly focused on producing a secure attendance marking system which is based upon one of the human gesture as Face. There are two stages to implement the approach. One is face detection using Haar classifier. Second one is face recognition using LHBP classifiers which is generated from trained faces.The proposed system is going to record the attendance of the people who are present in a classroom environment autonomously and this is an easiest way to produce the analysis and proof oriented approach makes as reliable applications.
Keywords: Haar-Classifiers, LHBP Classifiers and Smart Attendance, Reliable
Scope of the Article: Pattern Recognition