Abstract
Abstract: If attendance is managed manually, it can be quite taxing on the teachers. Smart and automated attendance management systems are being used to address this issue. This architecture makes it simple to address the issue of proxies and students being counted as present even though they are not. The system implemented makes use of the LBPH face recognizer to instantly recognise a person's face. Light has an impact on both Eigen and Fisher faces, and real-world lighting conditions cannot always be ideal. This issue can be solved by a change in the LBPH faces. This method decides who is present and who is not by comparing the images from the test and training sessions. A system-updated excel sheet that contains the attendance information is kept in the database. The faculty can get a copy of the attendance sheet through mail by clicking auto mail button in the GUI. The face recognizer detects faces using Haar Cascade Classifier, and recognizes the faces using Local Binary Patterns Histograms (LBPH) algorithm.
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