Machine learning classifier model for attendance management system

Face recognition technology has made many developments in the world. Attendance using face recognition is a real-time solution which involves handling of a person's attendance system. Face recognition based attendance system will be able to find and recognize human faces fast and precise in images or videos that are being captured through a camera. The traditional method of marking attendance is time-consuming and maintenance is difficult. There were so many methods like eigen faces, fisher faces etc. In this paper, the performance of face detection is implemented by a machine learning cascade classifier technique. It recognizes the faces in the image and compares it with the trained faces in the database. On identification of a registered face on the acquired image collections, the attendance of a person is registered automatically without manual interruption.