In the 21st century, everything around us has become depends upon technology to make our life much easier. Daily tasks are continuously becoming computerized. Nowadays more people prefer to do their work electronically. To the best of our knowledge, the process of recording students’ attendance at the university is still manual. Lecturers go through manual attendance sheets and signed papers to record attendance. This is slow, inefficient and time consuming. The main objective of this project is to offer system that simplify and automate the process of recording and tracking students’ attendance through face recognition technology. It is biometric technology to identify or verify a person from a digital image or surveillance video. Face recognition is widely used nowadays in different areas such as universities, banks, airports, and offices. We will use preprocessing techniques to detect, recognize and verify the captured faces like Eigenfaces method. We aim to provide a system that will make the attendance process faster and more precisely. The core problem is identified along with solutions and project path. Furthermore, detailed system analysis and design, user interface, methods and the estimated results are presented through our documentation.

Keywords: Attendance; Automate; Recording; biometric; face recognition;

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1.1 Introduction

“Office automation refers to the collective hardware, software and processes that enable automation of the information processing and communication tasks in an organization. It involves using computers and software to digitize, store, process and communicate most routine tasks and processes in a standard office.” [1]

In addition, attendance considered as the biggest issues that may face lecturers in class. It takes time, effort and difficult to manage. Therefore, our project will focus on online student attendance. In another word, the aim of this project is to build a system that help lecturers take students’ attendance in a professional way.

1.2 Problem Definition

Taking and tracking students’ attendance manually, losing attendance sheets, dishonesty, wasted time and high error scales are problems facing the lecturers use the existing attendance system. It is a hard process, take time and cause a lot of paper-based work. As a result, in order to solve these problems and avoid errors we suggest to computerize this process by providing a system that record and manage students’ attendance automatically without needing to lecturers’ interference.

1.3 Project Objectives

Our primary goal is to help the lecturers, improve and organize the process of track and manage student attendance and absenteeism. Additionally, we seek to:

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• Provides a valuable attendance service for both teachers and students.
• Reduce manual process errors by provide automated and a reliable attendance system uses face recognition technology.
• Increase privacy and security which student cannot presenting himself or his friend while they are not.
• Produce monthly reports for lecturers.
• Flexibility, Lectures capability of editing attendance records.
• Calculate absenteeism percentage and send reminder messages to students.

1.4 Project Scope

Our project targets the students of different academic levels and faculty members. The main constraint we faced is distinguishing between identical twins. This situation is still a challenge to biometric systems especially facial recognition technology. According to Phillips and his co-researcher paper [2] to get the best results of the algorithms your system employed, they should run under certain conditions for taken pictures (i.e… age, gender, expressions, studio environment…etc.) otherwise, the problem is still ongoing.

They provide application (method) to solve this problem, but in order to use this solution you have to sign a contract with the (NIST) organization and to be a researcher or developer. For us, to solve this issue we suggest to record twins’ attendance manually.

1.5 Contributions of This Study

We have searched for a system that can take, monitor and manage students’ attendance and absenteeism, send reminder messages, calculate absenteeism percentage, and produce weekly, monthly, and annual reports. Based on our searches, there is no integrated system can support our idea.

In this project, we are trying to develop such a system that can do all those tasks. Our project will serve students, lecturers, and the university as whole.

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1.6 Project Timeline

We utilized Gantt chart in figure 1.1, to show a project schedule with the start and finish dates of several tasks of a project and the deadline to submit the project.

1.7 Document Organization

This project consists of six chapters. These chapters organized to reflect the scientific steps toward our main objective. A brief description about the contents of each chapter given in the following paragraphs:

• Chapter 1 introduces the problem definition, project objectives, the contribution of this project, the scope of the work, and the project layout.
• Chapter 2 provides the reader with an overview of the literature review.
• Chapter 3 displays the analysis of the existing system, requirements elicitation which includes (functional requirements, nonfunctional requirements, User Requirements.), requirements specification, research methodology.
• Chapter 4 displays the architectural design, object oriented design figure.
• Chapter 6 displays the conclusion that includes limitation and future work.  

2.1 Introduction

Over the past decade, taking down students’ attendance process had been developed and changed.The driven force of this development is the desire to automate, facilitate, speed up and save time and efforts. Although that the attendance systems are around us everywhere, Taibah university lecturers still use a traditional way to record students’ attendance either through calling out students’ names or through a passing attendance sheet among students to sign beside their names. Both ways are time consuming and associated with high error scales. In this project, we attempt to reduce wasted time, eliminate buddy clocking, and automate the process. Our system uses facial recognition technology to record the attendance through a high resolution digital camera that detects and recognizes faces and compare the recognize faces with students’ faces images stored in faces database.

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Once the recognized face matches a stored image, attendance is marked in attendance database for that person. The process will repeat if there are missed faces. For example, if there are 4 faces missed for a bad position while the detecting phase, then this phase will start again to detect the missed faces and recognize them and continue the attending process. By the end of the month, a monthly report is send to the lecturer contains attendance and absence rates as a chart and the names of absentees. Also, a warning message sends to the student if he passes the allowed number of absence.

In this chapter, we present a brief overview of face recognition in the background section, relevant works to our project with their advantages and disadvantages, how we relate to these studies and how this project can provide some beneficial features for lecturer.

2.2 Background

Most lecturers have a significant number of students and it is hard to keep taking or tracking all their absence. Facial recognition is commonly used in many institutions to take attendance of a significant number of students. There are many errors that could occur during this process, including misidentification and self-recognition [3]. Lecturer can control the errors and correct it.

In the next subsection, brief overview of the usage,techniques, and methods in facial recognition.

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2.2.1 Face Recognition Usage

“Face recognition rises from the moment that machine started to become more and more intelligent and had the advance of fill in, correct or help the lack of human abilities and senses.” [4]. Common uses ofFacial recognition clarify in following points;

• Security; can be crime-fighting it will recognize people based on their eyes, nose and face.
• Searching for lost people.
• Games
• Taking student or employee attendance

2.2.2 Face Recognition Techniques and Methods

” Many factors influence the process of face recognition such as shape, size, pose, occlusion, and illumination. Facial recognition, have two different applications: basic and advanced “. Major face recognition recognizes faces or no faces such as balls and animals. If it is a face, then the system searches for eyes, a nose, and a mouth. Advanced facial recognition manages the question on a specific face. This contains unique landmarks: “the width of nose, wideness of the eyes, the depth and angle of the jaw, the height of cheekbones, and the separation between the eyes, and makes a unique numerical code.”

Utilizing these numerical codes, the system then matches that image with another image and distinguishes how comparable the pictures are to each other. The image provenance for face recognition include pre-existing pictures from various databases and video camera signals. [5]

A facial recognition system involves the following phases: Face detection, feature extraction, and face recognition as illustrated in Figure 2.1. [5]

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