DOIONLINE 
DOIONLINE Publish In |
International Journal of Advance Computational Engineering and Networking (IJACEN)-IJACEN |
 Journal Home Volume Issue |
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Issue |
Volume-12,Issue-7 ( Jul, 2024 ) | |||||||||
Paper Title |
Attendance Management System Using Face Recognition | |||||||||
Author Name |
Mariyam Mahboob, Nounman Mohsin Abdul Qadir | |||||||||
Affilition |
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Pages |
69-74 | |||||||||
Abstract |
Face recognition is one of the most effective image processing and pattern recognition applications. It is essential in the scientific community and provides numerous services. A face recognition attendance system uses high quality video monitoring to authenticate students using facial biostatistics. The creation of this system aims to digitally replace the outdated method of taking attendance by calling names and maintaining handwritten records. Both the current biometric systems and the conventional method of keeping attendance are vulnerable to proxies, lacking robust security measures. To solve this, we have utilized facial recognition techniques such as LBPH [Local Binary Pattern Histograms] and Haar Cascade algorithms. LBPH algorithms prove to be highly effective in handling facial variations due to changes in lighting, poses or expressions. Whereas Haar Cascade algorithms are mainly used for facial detection and ease of identification of facial regions within images or frames. Our system consists of five steps, including image capture, face detection, facial comparison, facial recognition, and updating attendance data in the database. By using the above techniques as well as rigorous testing under various conditions, our system is successful in accurately identifying students. Hence mitigating any susceptibilities for proxies. Overall, our system provides an accurate and simple use of face recognition to revolutionize old fashion techniques for attendance. Keywords - Pattern Recognition, Image Processing, LBPH algorithms, Haar Cascade Algorithms, Facial Recognition, Attendance Management. | |||||||||
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