Automated Student Attendance Management System Using Multiple Facial Images

Aditya Rama MITRA, Samuel LUKAS, Ririn Ikana DESANTI, Dion KRISNADI

Abstract


Nowadays, many applications such as video monitoring/surveillance system, humancomputer interaction, door access control system and network security use biometric authentication. One of the biometric identification is using fingerprint. it is considered to be the best and fastest method because every person has unique fingerprint and does not change in one's lifetime. Fingerprint recognition is a mature field today, but using face recognition technique is still better to be applied in capturing the present of the student in the class. Other advantages using face recognition are knowing the attitude of students in class such as students readiness or interestedness in lecture. This paper discusses a method for managing student attendance system in classroom using multiple facial images for classifying the facial objects. From the experiments conducted by involving 19 students situated in classroom setting, it results in 174 out of 205 successful faces recognition. Recognition rate is about 85%.

Keywords


Discrete biometric, Wavelet transform, Discrete cosine transform, Radial basis function neural network


DOI
10.12783/dtcse/cmsam2017/16422

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