• K Divya Sree
• P Ganesh
• N Revanth Krishna
• Dr. P Hemasree

Human face recognition plays an important role in applications such as video surveillance, human computer interface and face image database management. Our goal is to design a system that detects faces and facial features, and use these detected facial features as indices for identification. This system is developed by capturing real-time human faces. In our project we are introducing new convolutional neural network method to tackle the face recognition to maintain a high accuracy while running in real time. This System can be used in Government Schools and Colleges to monitor and validate attendance. This process is carried out for every employee and is given attendance accordingly. The person will be enrolled to the database using their unique id (captured with persons audio) with sufficient number of face images each. The information will be stored in the folder. Image captured in the previous stage is taken as input in this stage. Face detection and recognition are performed followed by face alignment and the aligned faces are cropped. Local (LBP) and Global (HOG) features are extracted and trained using Haar Cascade Classifier for detection and SVM is used for face recognition. After training the system on the database our system is placed in the room. Camera is adjusted in such a way that all the employees’ faces are visible. Finally, for the captured image, Face Recognition is performed on stored database and attendance is recorded.

Raspberry pi processor, Face recognition using CNN, Camera, LCD display, Buzzer and Microphone.

"Employees Attendance Management using Face Recognition", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.9, Issue 8, page no.d9-d14, August-2022, Available :http://www.jetir.org/papers/JETIR2208302.pdf

"Employees Attendance Management using Face Recognition", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.9, Issue 8, page no. ppd9-d14, August-2022, Available at : http://www.jetir.org/papers/JETIR2208302.pdf