Automated Attendance Systems Using Face Recognition by K-Means Algorithms
N. Palanivel, S Aswinkumar, Janani Balaji · 2019 IEEE International Conference on System, Computation, Automation and Networking (ICSCAN) · 2019
Attendance plays a crucial role in educational institutions, several of the other industries and workplaces. Nowadays it's taken by standard methodology i.e. Attendance are taken manually. This method takes a great deal of your time and additionally there might be an error. Face recognition system could be a technology capable of distinguishing or confirming someone from a digital image or from a video supply. In this paper, we tend to build a system that marks the presence of students or employees by recognizing their faces and manufacturing the attending sheet automatically. Face Recognition's accuracy rate is definitely littered with the factors like changes in illumination, posture changes, expression changes, and occlusion. In this paper, a K-means clustering algorithmic rule is employed to research the facial expression. The biometric features of the face unit are extracted and also the K-mean clustering technique is used to cluster the face features. Then, SVM methodology is employed to classify the features of the image. It may accomplish high recognition performance with fewer feature numbers. Finally, a report (attendance sheet) is generated for interpretation.