Abstract:

The implementation of a Facial Recognition System can aid in identifying or verifying a person's identity from a digital image. Accurate attendance records are vital to classroom evaluation. However, manual attendance tracking can result in errors, missed students, or duplicate entries. The adoption of the Face Recognition-based attendance system could help eliminate these shortcomings. This innovative approach involves utilizing a camera to capture input images, detecting faces using algorithms such as Haarcascade, Eigen values, support vector machines, or the Fisher face algorithm, verifying the faces against a database of student profiles, and marking attendance in an Excel sheet. The use of OpenCV, an open-source computer vision library, ensures the efficient functioning of the system. The proposed model involves training the system with the authorized students' faces to create a database. The system crops and stores the images in a database with corresponding labels and extracts features using algorithms such as LBPH, Haarcascade, Eigen values, support vector machines and Fisher face algorithm. The Face Recognitionbased attendance system could help automate attendance records with high accuracy and reduce the burden of manual attendance tracking

Description:

Open CV, LBPH, Haar Cascade