ABSTRACT
In recent time students are currently adopting various examination malpractice method. The most rampart
among the approach is impersonation which cannot be easily detect especially in a very large class and conspiracy
of some invigilator or teachers. This research is focused on design of biometric control examination attendance
register to deter impersonation during examination. There are various approach to biometric usage which include
the fingerprint, face recognition, DNA, hand geometry, iris recognition, retina etc. This research work adopted
face recognition biometric technology that recognized different faces. Database of the captured image was built
through the use of K-means/hierarchical algorithm model and EM algorithms to initiate and refining the database
model respectively. Face recognition was done via skin segmentation, candidates face search, and verification,
while face recognition was carried out by face image processing and classification. The entire process was coded
using java.net and the resulted system was tested with return shows significant accuracy of recognition test for
candidate/students used in the training and testing phase.
Keywords: - Biometric control, deep learning algorithm, examination malpractice, Face Detection and Recognition.