• Nichenametla Venkata Sai Priya
• Dr. T.Ramashree

: This work proposes a silent face attendance system utilizing a Mobile Net Classifier model for liveness detection. The system addresses the challenge of distinguishing real faces from spoofed images (e.g., prints, masks) without requiring user interaction.In this work,we use a combination of Haar Cascade algorithms and MobileNet classifiers to identify live faces. Our system has three modes: registration, login/logout, and spoof detection. During registration, the system only accepts and stores real faces in the database. For existing users, the system records attendance details when it recognizes a genuine face. If a spoof attempt occurs, the system quickly notifies the user with a spoof detection message. By comparing Python-based software between classifiers, we have shown the efficiency and reliability of our method. This integration not only secures the attendance system against spoofing attacks but also records it and provides a smooth and secure user experience, opening doors for future research and advancements in biometric authentication and Local Binary Pattern histogram (LBP) is used for detecting and recognizing human faces in proposed system. It is based on local binary operator, and it is one of the best performing texture descriptors.Suppose consider an image which having dimensions N x M. For every region in an image, we have to divide it into regions of same height and width resulting in m x m dimension

Silent face recognition, Anti-spoofing, Liveness detection, Haar Cascaded Classifier, Mobile Net Classifier

"Silent Face Anti-Spoofing Liveliness Detection Attendance System", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.11, Issue 7, page no.e688-e695, July-2024, Available :http://www.jetir.org/papers/JETIR2407475.pdf

"Silent Face Anti-Spoofing Liveliness Detection Attendance System", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.11, Issue 7, page no. ppe688-e695, July-2024, Available at : http://www.jetir.org/papers/JETIR2407475.pdf