• kesani bhargav
• chakrala vamshi
• konakala sambasivarao
• betha veera nagi reddy

: Marking Attendance is probably the most typical way to know the actual physical presence of a person. Though it's difficult with regards to a mechanical attendance process, Day by Day the amount of pupils in schools & universities is growing thus, which makes it harder in controlling & maintaining the attendance records. Automation is the demand in each and every sector to minimize human effort. Personal computer vision is a component of automation wherein pc replicates the man vision structure and performs an understanding of info that is helpful from pictures. It's a boon for a lot of issues, attendance product could additionally be converted from hand-operated sheets to confront recognition. This particular paper proposes a framework for building an attendance structure by using Face Recognition. This particular process comprises a webcam which may be interfaced to PC Android. the digicam may be unlocked to record pictures. Every student's image is shot as well as saved for instruction. OpenCV is needed with a machine learning algorithm to find faces inside one picture. When faces can be found it's qualified using KNN algorithm. New pictures are in contrast to preexisting pictures kept in the website utilizing the KNN algorithm. Attendance is instantly recorded once the faces are coordinated, if not possibly the pupil is new or maybe the pupil is not coming from the category. In this particular manner precision is maintained, therefore making the attendance process simpler & economical.

Face Detection, Face Recognition.

"COMPUTER VISION BASED AUTOMATED ATTENDANCE SYSTEM", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.8, Issue 5, page no.a957-a960, May-2021, Available :http://www.jetir.org/papers/JETIR2105122.pdf

"COMPUTER VISION BASED AUTOMATED ATTENDANCE SYSTEM", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.8, Issue 5, page no. ppa957-a960, May-2021, Available at : http://www.jetir.org/papers/JETIR2105122.pdf