Abstract:
Taking attendance of students is one of the foremost tasks in a class for teachers at the same
time pretty much complicated. The manual attendance system takes an enormous amount
of time over the number of students and has a prospect of being a proxy. Day by day it’s
getting really intimidating as the number of students is increasing. Last few years
automated biometric like a fingerprint, QR-code technology has developed. However, time
makes the difference here with facial recognition technology
The proposed attendance system can take attendance by detecting and then recognizing the
face. This system can make a crystal clear concept to the machine whether it’s a legal
attendance or proxy. More secured and hassle-free system. In this system, all the student’s
data with time and class-wise will be saved in the database. So that teacher can easily
evaluate his/her students in marking on attending. Also, help the teacher to inform
individuals' parents whether or not their son/ daughter regular in the class.
In this proposed system we used an effective machine learning-based object detection
method Haar feature-based cascade classifiers proposed by Paul Viola and Michael Jones
for classifying extracting images and for recognizing LBPH used in this system.