Face Recognition in e-attendance

Project Name: Face Recognition in e-attendance

Purpose: TO implement e-attendance using eigen face algorithm

Project Description:       

Recently face recognition is attracting much attention in society of network multimedia information access .Areas such as network security, content indexing and retrieval and video compression benefits from face recognition technology because “people” are the centre of attention in a lot of video .Network access control via face recognition not only makes hackers virtually impossible to steal one’s “password”, but also increases the user –friendliness in human-computer interaction.

A training set consists of face images from which a set of eigen faces can be generated by performing a mathematical process called principal component  analysis(PCA) on a large set of images depicting   different human faces .The eigenfaces can be used to represent both existing and new faces we can project a new(mean-subtracted) image on the eigenfaces and thereby record how that new face differs from the mean face .The eigen values  associated with each eigenface represent how much the images in the training set vary from the mean image in that direction .We lose information by projecting the image on subset of the eigen vectors ,but we minimize this loss by keeping those eigen faces with the largest eigen values .      

                     

In this way each student’s input image is matched with the training set image. If a match is found attendance is marked as present else marked as absent for that particular student. This overcomes proxy, identifies punctuality of students and also recognizes lecturers and their punctuality and regularity in handling classes. Administration can know about handling of classes at its chair.