Face recognition-based attendance system using real-time computer vision algorithms

Abstract

The face identification system is one of the most emerging methods for authentication of user; it is drawing wide attraction to the surveillance system which reflects innovation in a video surveillance system. This system here represents the automated attendance system using real-time computer vision algorithms and adaptive techniques to track the faces during a specific period of time. Our system works on eigenface recognizers and Intel’s Haar cascades which make the attendance-taking process easier and less time-consuming rather than the traditional process. Our system provides the cheapest solution rather than a previous biometric system like fingerprint authentications. The recorded data is being compared with the training dataset, and the attendance is recorded if the match is found with the help of Python libraries. The camera is being installed at the entry location, so that attendance is recorded as soon as the match of the person entering the particular area is found. So, our main aim is to provide an alternative which is very much convenient to process the attendance and also is very much safe and authentic to have faced as a security option.