Nowadays face recognition topic is attracting more attention in the society of network multimedia information access. Normally in all videos, people are centre of attraction. Network security, content indexing & retrieval and video compression benefits are the areas of the face recognition technology. The benefits of the face recognition technology are given below:

• It increases the user -friendliness in human-computer communication.
• It protects the password of a person from the hackers.

We can generate a set of Eigen faces from a training set of face images by performing a mathematical process called principal component analysis (PCA) on a large set of images showing different human faces. By using Eigen faces, we can represent both existing faces and new faces. By projecting a new (mean-subtracted) face on the Eigen faces, we can record the difference between the new face and the mean face. The Eigen values associated with each Eigen face will represent how much the mean image in that direction vary from the images in the training set. By projecting the image on subset of the Eigen vectors, we will lose the information. But we can reduce this loss by keeping those Eigen faces with the largest Eigen values.

In this way, this system matches the input image of each student with the training set image. If match is found then it will mark the attendance of a particular student as present and it will mark as absent if match is not found. By this administrator of a school/college can identify the punctuality of students. Also he can recognize the lecturers, their regularity in handling classes and punctuality. He can know the details about handling of classes.

Purpose:

Main purpose of this project is to implement e-attendance using Eigen face algorithm.

The researcher will study about the fundamentals of face detection techniques, image processing and face recognition techniques during the system research. After analysing these techniques, he will select the appropriate techniques for extracting partial face regions and to identify the individuals. The document includes introduction, system research, requirement specification, domain research, technical investigation and project development plan.

At the end, appropriate image processing techniques, face recognition techniques and face detection techniques are selected and they are justified along with selection of project developing platforms and project developing methodologies.

This face recognition system recognizes the individuals based on characteristics of separate face segmentations.

• Investigation about the unique face features of eye, nose and mouth regions are useful in recognizing the individuals. But, when it come to separate face regions there are only few unique features that help the user to identify the individuals.
• Improving the capabilities of the detecting features of local segmentations of face: Identifying the efficient algorithm to extract features of the face segmentations is very important.
• Implementation of the robust, efferent face recognition system based on the facts that found in the research.

-are the main objectives of this project.