A Review: College Attendance System Using Image Tagging

Abstract

Image tagging is the method of applying labels or keywords to a provided image to the recognized faces or objects. Facial recognition is a category of biometic software which maps a person’s facial features mathematically and stores the data as a information related to the face. Facial recognition is the concept, which uses several machine learning algorithms, to compare a given face with the pool of known faces to find the identity of the person. The typical register attendance program requires the participation of teachers as well as students as it takes time to identify and mark every student and it is vulnerable to mistakes because any student attendance may be overlooked by the faculty as well as proxies can also be done. Biometric scanning or manual attendance labelling in log book are the traditional methods to monitor student attendance; however, they are time-consuming , fallible and costly method that does not fully limit the involvement of proxies. In this paper, we introduced the use of face tagging in a real-time attendance system to resolve time wastage in biometric scan and overcoming all the disadvanatges of conventional manual attendance schemes. This system is designed primarily to take a picture of the entire class and identify all students simultaneously. The student’s tagged face marks the attendance. Along with the tagging and attendance marking, the system is also able to monitor the total attendance of any student with statistical results. The presence is labelled on the basis of the stored picture, so that a proxy involvement is excluded. The main goal of the project is to make maximum use of lectures time by reducing wastage of time in marking and monitoring of the attendance using traditional schemes, thereby minimizing human interference.