ISSN (Online) : 2456 - 0774

Email : ijasret@gmail.com

ISSN (Online) 2456 - 0774

FACE ATTENDENCE SYSTEM

Abstract

Abstract— Recent advances in the performance of automatic face recognition (AFR) systems have made them widely applicable for a variety of security and commercial applications. An Human facial recognition is utilised in real time by corporations to keep track of employee attendance. So Face recognition in real time for smart attendance is a practical use. Managing staff on a daily basis necessitates a system like this. Real-time image background subtraction is still a problem, making this a difficult operation. Real-time recognition of a human face. both basic and fast methods are put to use An analysis method known as Principal Component Analysis (PCA) has been employed to Recognize the faces that were detected with a high degree of accuracy. The coordinated The face of the employee is used to track their attendance. Our technology automatically keeps track of employee attendance. Manual Data entry into logbooks becomes time consuming and complex. the time span Because of this, we were able to design a useful module that includes a face Recognition is used to keep track of employee attendance. Our There is a module in which the employee's face is included. Once you've completed the enrollment form, you're done. The database will have a photo of them. As part of the application procedure, We need a system because this is a one-time event. Having fun is something you can do. roll number, which will be your own employee id. every every worker The presence of each employee will be regularly updated. database. Manual performance was shown to be inferior when compared to automatic performance. Tracking system for people's presence. The time an employee spends at work is recorded after they have been identified. There are a lot more choices with this product. With this approach, correct results are provided in a user-interactive manner, as opposed to traditional systems for managing attendance and leave. Keywords:- haar cascade, Preprocessing, Feature Extraction.

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