Attendance System using Face Recognition

Abstract—In the current educational system, student’s frequent attendance in class is very important for performance evaluation and quality control. Most institutions still use insecure, time-consuming traditional methods like calling people by name or having them sign documents. Face recognition technology based on high-definition monitor video other information technologies used to solve problem of recognizing face taking attendance. A facial system uses automatically record while identifying verifying a person their features. This research focusing recognition-based with getting less false- positive rate using threshold confidence i.e., Euclidean distance value detecting unknown persons save images. Compare distance-based algorithms Eigenfaces Fisher faces, Local Binary Pattern Histogram (LBPH) algorithm better. We Haar cascade detection because robustness LBPH recognition. It robust against monotonic grayscale transformations. Scenarios such as rate, that false-positive without are considered evaluate our system. got students 77% its 28%. even when wearing glasses grown beard. Recognition nearly 60% both applying value. Its 14% 30% respectively. Keywords—Face recognition, detection, machine learning, Cascade Algorithm, Pattens Histograms (LBPH).