GUJARAT TECHNOLOGICAL UNIVERSITY
VADODARA INSTITUTE OF ENGINEERING
A Report on:-
AUTOMATED ATTENDANCE SYSTEM BASED ON FACIAL RECOGNITION
Under subject of
B.E. 3, Semester – 5
(Computer Engineering Branch)
Sr. Name of student Enrolment No.
1 Nanavati Param 160800107037
2 Bhosale Vedant 160800107013
3 Limbachia Shreyansh 160800107032
Prof. DIMPLE S KANANI PROF. AJAYSINH RATHOD
(Faculty Guide) (Head of the Department)
VADODARA INSTITUTE OF ENGINEERING
COMPUTER ENGINEERING DEPARTMENT
(2018 – 2019)
This is to certify that the Project entitled “AUTOMATED ATTENDANCE SYSTEM BASED ON FACIAL RECOGNITION” has been carried out by Nanavati Param(160800107037), Bhosale Vedant(160800107013) And Limbachia Shreyansh(160800107032) under by guidance in fulfilment of the degree of Bachelor of Engineering in Computer Engineering 5th Semester of Gujarat Technological University, Ahmedabad during the academic year 2018-2019.
(Prof. Dimple Kanani) (Prof. Ajaysinh Rathod)
Internal guide Head of the Department
It is very difficult to express our feelings and we feel short of words for those who have contributed a lot in our training and provided their invaluable cooperation to us. Many people have helped, provided direction as well as technical information and it is our pleasure to acknowledge our debt to the many people involved directly or indirectly involved in development of this project.
Our deep sense of gratitude is extended to Prof. Dimple Kanani whose continuous Encouragement, suggestion, and constructive criticism have been invaluable assets throughout the project work.
We would like to offer special thanks to Vadodara Institute of Engineering for helping us to build our career and laying down a platform, which will help us to build a career in software industry.
Nowadays Educational institutions are concerned about regularity of student attendance. This is mainly due to students’ overall academic performance is affected by his or her attendance in the institute. Mainly there are two conventional methods of marking attendance which are calling out the roll call or by taking student sign on paper. They both were more time consuming and difficult. Hence, there is a requirement of computer-based student attendance management system which will assist the faculty for maintaining attendance record automatically.
In this project we have implemented the automated attendance system using MATLAB. We have projected our ideas to implement “Automated Attendance System Based on Facial Recognition”, in which it imbibes large applications. The application includes face identification, which saves time and eliminates chances of proxy attendance because of the face authorization. Hence, this system can be implemented in a field where attendance plays an important role.
The system is designed using MATLAB platform. The proposed system uses Principal Component Analysis (PCA) algorithm which is based on Eigen face approach. This algorithm compares the test image and training image and determines students who are present and absent. The attendance record is maintained in an excel sheet which is updated automatically in the system.
No. Title Page no.
1. INTRODUCTION 1
2. EMPATHY MAPPING 2
2.1 Formation of canvas 2.2 Users 2.3 Stockholder 2.4 Activities 2.5 Story Boarding 3. AEIOU CANVAS 5
3.1 Activities 3.2 Users 3.3 Environment 3.4 Interaction 3.5 Objects 4. IDEATION CANVAS 8
4.1 people 4.2 Activities 4.3 Situation/Context/Location 4.4 Props/Possible Solutions 5. PRODUCT DEVELPOMENT CANVAS 10
5.1 Purpose 5.2 Product Experience 5.3 Product Functions 5.4 Product Features
5.5 People 5.6 Components
5.7 Customer Revalidation
6. MIND MAPPING CANVAS 13
7. LNM CANVAS 14
8. PROTOTYPE MODEL 15
9. FUTURE ENHANCEMENT 16
10. CONCLUSION 17
11. REFERENCES 18
LIST OF FIGURE
Figure No. Figure Name Page No.
Fig 2.1.1 Empathy Mapping 4
Fig 3.1.1 AEIOU Canvas 7
Fig 4.1.1 Ideation Canvas 9
Fig 5.1.1 Product Development Canvas 12
Fig 6.1.1 Mind Mapping 13
Fig 7.1.1 LNM Canvas
Fig 8.1.1. Prototype model 15
Introduction to domain/project
In the recent years, Image processing which deals with extracting useful information from a digital image plays a unique role in the advent of technological advancements. It focuses on two tasks • Improvement of pictorial information for human interpretation • Processing of image data for storage, transmission and representation for autonomous machine perception. Also people have started to use image capturing devices never as before with the advent of smart phones and closed circuit television. Since the application of image processing is vast, extensive work and research have been carrying out in utilizing its potential to and to make new innovative applications. Facial recognition has been the earliest of the application derived from this technology, which is one of the most fool proof methods in human detection. Face is a typical multidimensional structure and needs good computational analysis for recognition. Biometrics methods have been used for the same purpose since a long time now. Although it is effective, it is still not completely reliable for purpose of detecting a person.
This exercise allows us to better analyse the desires and needs of the users like student’s faculties and in the process uncover previously unseen or noticed ways to improve a service. It’s a very simplistic way to identify and reduce the potential hurdles, we are better able to please our customer.
formation of canvas
the users of this product
stake holder of this product
Activities performed by this product
The possibilities of happy and happening in terms of stories.
As manual attendance wastes time of lectures and is an extra task for faculties it is not much convenient. Wish the advent of small attendance, this load on facilities decreases and causes complete on time.
Once there was a professor in is collage, who did not like to waste any single second of his lecture. So, he found it very time wasting to take the attendance. As he was of a modern minute, he wanted something to ease his effort.
As attending lecture for continuous one hour for students is hectic. As student gets 10 minutes free when faculty takes attendance, though automatic attendance will takes free 10 minutes from students.
Fig 2.1.1 Empathy Mapping
It is a framework that includes Activities, Environment, Interaction, Object and User.
Fig. 3.1.1 AEIOU Canvas
Ideation means generate new ideas. Ideation is the creative process of generating, developing and communicating new ideas, where as an idea is understood as a basic element of thought that can be visual, concrete, or abstract. Ideation comprises all stage of a thought cycle, from innovation, to actualization. As such, it is an essential part of the design process both in education and practice.
Fig. 4.1.1 Ideation Canvas
PRODUCT DEVELPOMENT CANVAS
Production canvas is the overview of product we are making. In this we will start building a structure of our product around the users. It is a strategic product planning tool that allows us to quickly capture, describes and pivot our product strategy on a single page.
No time consume
By increasing range
Fig. 5.1.1 Product Development Canvas
MIND MAPPING CANVAS
A mind map is a visual representation of hierarchical information includes a central idea surrounded by the connected branches of associated topics.
Mind mapping is highly effective way of getting information in and out of your brain. Mind mapping is a creative and logical means of note taking and note making that latterly “maps out” your idea.
Fig. 6.1 Mind Mapping
Describes: – The LNM is containing a quadratic layout. From centre (the concept under development), it needs to have mention of learning/exploring requirements in each quadrant representing a specific type of skill acquisition. These quadrants have a timeline associated with it that can be considered in the year of studies (II, III and IV) or phases as (short-term, mid-term and long-term). Each identified requirement of learning is connected depending upon interdependencies and paths are to be drawn. The team members can develop their own learning path to contribute to the efforts of the team for developing the concept underlying at the centre of the LNM.
Fig. 7.1.1 LNM Canvas
Fig. 8.1.1 Prototype Model
The system we have developed has successfully, able to accomplish the task of marking the attendance in the classroom automatically and output is obtained in an excel sheet as desired in real-time. However, in order to develop a dedicated system which can be implemented in an educational institution, a very efficient algorithm which is insensitive to the lighting conditions of the classroom has to be developed. Also a camera of the optimum resolution has to be utilised in the system. Another important aspect where we can work towards is creating an online database of the attendance and automatic updating of the attendance into it keeping in mind the growing popularity of Internet of Things. This can be done by creating a standalone module which can be installed in the classroom having access to internet, preferably a wireless system. These developments can greatly improve the applications of the project.
In this system we have implemented an attendance system for a lecture, section or laboratory by which lecturer or teaching assistant can record students’ attendance. It saves time and effort, especially if it is a lecture with huge number of students. Automated Attendance System has been envisioned for the purpose of reducing the drawbacks in the traditional (manual) system. This attendance system demonstrates the use of image processing techniques in classroom. This system can not only merely help in the attendance system, but also improve the goodwill of an institution.
1 M. T. a. A. Pentland, “Eigenfaces For Recognition,” Journal of Cognitive Neuroscience, vol. 3, no. 1, 1991.
2 A. V. a. R. Tokas, “Fast Face Recognition Using Eigen Faces,” IJRITCC, vol. 2, no. 11, pp. 3615-3618, November 2014.
3 Paul Viola and Michael J. Jones, “Robust Real-Time Face Detection,” International Journal of Computer Vision, vol. 57, no. 2, pp. 137-154, May 2004.
4 N. J. M. M. K. a. H. A. Mayank Agarwal, “Face Recognition Using Eigenface aproach,” IRCSE, vol. 2, no. 4, pp. 1793-8201, August 2010.
5 Vinay Hermath, Ashwini Mayakar, “Face Recognition Using Eigen Faces and,” IACSIT, vol. 2, no. 4, pp. 1793-8201, August 2010.