Loading

Automatic Attendance System with Face Recognition using Machine Learning
T. Nagamani1, S. Logeswari2, B. Gomathy3, P. Sathishkumar4, K. V. Kiruthikaa5

1Nagamani T.*, Department of CSE, Bannari Amman Institute of Technology, Erode, India.
2Dr. S. Logeswari, Department of CSE, Bannari Amman Institute of Technology, Erode, India.
|3Dr. B. Gomathy, Department of CSE, Bannari Amman Institute of Technology, Erode, India.
4Mr. P. Sathishkumar, Department of CSE, Bannari Amman Institute of Technology, Erode, India.
5Mrs. K. V. Kiruthikaa, Department of CSE, Bannari Amman Institute of Technology, Erode, India.
Manuscript received on March 12, 2020. | Revised Manuscript received on March 25, 2020. | Manuscript published on March 30, 2020. | PP: 3642-3646 | Volume-8 Issue-6, March 2020. | Retrieval Number: D9516118419/2020©BEIESP | DOI: 10.35940/ijrte.D9516.038620

Open Access | Ethics and Policies | Cite | Mendeley
© 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: Object and Face detection and recognition is one of the mostly researched area in computer vision. This particular field of work is widely used in mobile phones and laptops for unlocking the system by the user. Recently this field gained importance in the automatic attendance system in schools, colleges and institution. The institutions are moving from biometric based attendance to face recognition based attendance system. In this project work, I have used machine learning techniques to create a complete system of automatic attendance system which can be implemented very easily. There are majorly four steps involved in the system. Firstly, the datasets can be created instantly using webcam and in the second stage the created data set have to be trained and the trainer algorithm will create the trainer.yml document. As a next step, the face recognition algorithm have to be performed in order to recognize the faces of various students and teacher. In the final step, the attendance of the students will be updated in the CSV file or Excel. The proposed work is very much suited for the real time applications like automatic attendance system. HaarCascade is very effective technique to produce much simple and accurate system.
Keywords: Face Recognition, Haarcascade, LBPH.
Scope of the Article: Machine Learning.