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dc.contributor.authorIslam, Jahurul
dc.contributor.authorHoque, Md. Siamul
dc.contributor.authorAhmed, Md.Tahmid
dc.contributor.authorHasan, Md. Rakibul
dc.contributor.authorMia, Md.Insan
dc.date.accessioned2023-10-09T04:44:06Z
dc.date.available2023-10-09T04:44:06Z
dc.date.issued2023-05-15
dc.identifier.urihttp://suspace.su.edu.bd/handle/123456789/637
dc.description.abstractTo maintain the attendance record with day to day activities is a challenging task. The conventional method of calling name of each student is time consuming and there is always a chance of proxy attendance. The most demanding task in any organization is attendance marking. In traditional attendance system, the students are called by the teachers and their presently or absently is marked accordingly. However, these traditional techniques are time consuming and boring. The following system is based on face recognition to maintain the attendance record of students. The daily attendance of students is recorded subject wise which is stored already by the administrator. As the time for corresponding subject arrives the system automatically starts taking snaps and then apply face detection and recognition technique to the given image and the recognize students are marked as present and their attendance update with corresponding time and subject id. The system’s major goal is to identify and recognize faces in a real-time environment, match them with data in the database, and record their attendance. This is intended to make the time-consuming manual attendance process more efficient. This also overcomes the issue of authentication and proxies because biometrics is one-of-a kind, and facial traits used for Face Recognition are one of them. For face detection and recognition, the designed system uses OpenCV, dlib, Face Recognition libraries, and One-Shot Learning, which takes just one image per person in the database and so saves space when compared to standard training-testing models. The cropped images are then stored as a database with corresponding labels. The features are extracted using LBPH algorithm.en_US
dc.language.isoenen_US
dc.publisherSonargaon University (SU)en_US
dc.subjectAttendance Systemen_US
dc.subjectSmarten_US
dc.titleDesign and Implementation of a Smart Attendance System (SAS)en_US
dc.typeThesisen_US


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