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Abstract: An image or video that was captured using a digital camera can be used to discover, track, identify, or verify human faces using a computer program called face recognition. The time-consuming, inaccurate, and traditional attendance techniques are to be replaced by this system. The suggested system uses a camera to take pictures of people, then uses an artificial neural network to recognize and compare facial characteristics. Administrators and teachers can easily watch student attendance records anywhere because the system generates attendance reports in real-time. Here, we introduce a novel approach that combines the Local Binary Pattern (LBP) algorithm with cutting-edge image processing methods like Contrast Adjustment, Bilateral Filter, and addressing some of the problems affecting the accuracy of face recognition, such as histogram equalization and image blending, the LBP codes are improved, which raises the accuracy of the face recognition system. Our test findings demonstrate that our approach is highly accurate, dependable, and robust for a face recognition system that can be used as a Face Recognition Attendance System in a real-world setting.