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Abstract: This model aims to provide a robust and efficient real-time face attendance recognition solution utilizing the Haar Cascade algorithm. With the increasing demand for automated attendance systems, it leverages advanced facial recognition technology to streamline the attendance process, offering a seamless and contactless experience. The system captures real-time video input, processing each frame to detect and recognize faces using the Haar Cascade algorithm, complemented by an Anti-Spoofing Technique. This approach enables rapid and accurate face detection across varying lighting conditions and poses. Detected faces are then compared against a pre-registered database to automatically identify individuals and mark their attendance. Our proposed system not only minimizes manual errors but also features a user-friendly interface that can be easily adapted to diverse environments, making it an effective tool for modern attendance management.