Automatic Attendance System Using Face Recognition Technique
Mayur Surve1, Priya Joshi2, Sujata Jamadar3, Minakshi Vharkate4
1Mayur Surve, Student, Department of Mechanical Engineering in MIT Academy of Engineering, Pune, India.
2Priya Joshi, Student, Department of Mechanical Engineering in MIT Academy of Engineering, Pune, India.
3Sujata Jamadar, Student, Department of Mechanical Engineering in MIT Academy of Engineering, Pune, India.
4Mrs. Minakshi N. Vharkate, Sr. Assistant Professor, Department of Computer Science and Engineering, School of Computer Engineering and Technology, MIT AOE, Alandi (D), Pune, India.
Manuscript received on April 30, 2020. | Revised Manuscript received on May 06, 2020. | Manuscript published on May 30, 2020. | PP: 2134-2138 | Volume-9 Issue-1, May 2020. | Retrieval Number: A2644059120/2020©BEIESP | DOI: 10.35940/ijrte.A2644.059120
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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: Attendance system is very important in schools and colleges’ Manual attendance system has many difficulties like it may less accurate and critical to maintain. So, attendance system using face recognition technique increase the accuracy and also it required less time than other methods. There are many existing system for attendance such as face recognition using IoT, PIR sensors and so on. For face recognition, hardware devices also helpful. But challenge is that to maintain all the sensors properly without get damage. After studying all method and techniques we are trying to implement a system with Haar Cascade Algorithm which has highest accuracy among all. It is able to capture the images from 50-70cm. We are creating graphical user interface which capture the images, create the dataset and train the dataset on single click. After recognizing the face it will display name of student and roll number. That information stored in attendance sheet automatically with time and date.
Keywords: SFace Detection, Face Recognition, Haar Features, Histogram of Oriented Gradient
Scope of the Article: Face Recognition