Face Recognition And Qrcode Attendance Taken And Verification System Using Deep Learning Approach:-Akoma, Knowledge P.

Akoma Knowledge PAUL | 86 pages (13918 words) | Projects

ABSTRACT

Face Recognition and QRCode Attendance taken and Verification system using deep Learning Approach, this is an artificial intelligence platform for security purposes. The approach is a system designed to improve the security system of financial institutions. The project work focuses on two authentication systems face recognition and credit card verification. The issue of theft, i.e. an authorized person having access to the financial properties of another has been in great disaster to the advancing digital system. The problem faced by credit card users is vulnerability to a lot of privacy issues such as credit card parameters. This may commonly occur when users give their credit card numbers to unfamiliar individuals or when cards are lost. Our solution proposes a technique by which the features extracted from the image clicked during the payment made by a user on an e-commerce portal will be compared to the features from the training dataset of the respective user. Features extracted from the Images stored in the administrator database acts as the training data set for authentication purpose. The project implementation employed the methodology of the spiral model of software development life cycle with a reason that the system implements an iteratively and the framework is python flask, the programing language used python and the database model user is sqlite3. The web-based platform was tested, and the administrator side registered the user, and take pictures and datasets. The user’s credit card identification and facial recognition were tested with more than two and it was able to identify them separately and give them access to their respective dashboards/account.

 

 

 

 

 

 

 

 

 

 

 

 

 

 

TABLE OF CONTENT

Front Page                                                                                                                               i

Certification                                                                                                                            ii

Dedication                                                                                                                              iii

Acknowledgement                                                                                                                  iv

Abstract                                                                                                                                  vi

Table of Content                                                                                                                     vii         

List of Tables                                                                                                                          xi

List of Figures                                                                                                                         xii

CHAPTER 1: INTRODUCTION

1.1 Background of the Study                                                                                                 1

1.2 Statement of the Problem.                                                                                                6

1.3  Aims and Objectives of the Study                                                                                   6

1.4 Significances of the Study                                                                                                7

1.5 Scope of the Study                                                                                                           8

1.6 Definition of Terms                                                                                                          8

CHAPTER 2: LITERATURE REVIEW

2.1 Concept of Face Identification and Verification                                                             9

2.2 Conceptual Framework                                                                                                     9

2.3 Theoretical Framework                                                                                                     10

2.3.1 Facial Recognition Technology                                                                                     11

2.3.2 Biometrics and Identification in a Global Web                                                             13

2.4 Empirical Framework                                                                                                        16

2.4.1 Face Recognition Operation                                                                                          16

2.4.2 FRS Tasks and Verification                                                                                           18

2.5 Summary of Previous Related Literature Review                                                            20

2.6 Knowledge Gap                                                                                                                22

CHAPTER 3: SYSTEM ANALYSIS AND RESEARCH METHODOLOGY

3.1 Analysis of the Existing System                                                                                       24

3.1.1 Advantage of the Existing System                                                                                24

3.1.2 Disadvantage of the Existing System                                                                            25

3.2 Analysis of the Proposed System                                                                                     25

3.2.1 Advantage of the Proposed System                                                                              27

3.3 Research Methodology                                                                                                     28

3.3.1 Data Collection Methods                                                                                               32

3.3.2 Adopted Research Methodology                                                                                  35

3.3.3 Component of the Adopted Research Methodology                                                    36       

3.3.4 System Investigation                                                                                                     37       

3.4 Justification of the Newly Proposed System                                                                    38

CHAPTER 4: SYSTEM DESIGN AND IMPLEMENTATION

4.1 Objective of the New System                                                                                           40       

4.2   Decomposition and Cohesion of the High-Level Model                                                41       

4.2.1 Main Menu                                                                                                                     41

4.2.2 The Sub-Menus                                                                                                              42

4.3 Specification                                                                                                                     43       

4.3.1 Database Specification                                                                                                  44       

4.3.2 Input/output Format                                                                                                      47

4.3.3 Use Case Diagram                                                                                                         49

4.3.4 Algorithmic Operational Process                                                                                   50       

4.3.5 Data Dictionary                                                                                                             51

4.4 Flowchart                                                                                                                          53       

4.5 New System Requirement                                                                                                            55       

4.5.1 Hardware Requirement                                                                                                  55       

4.5.2 Software Requirement                                                                                                   56       

4.6 Program Development                                                                                                      56       

4.6.1 Choice of Program Environment                                                                                   56

4.6.2 Language Justification                                                                                                   56

4.7 System Testing                                                                                                                  57

4.7.1 Testing Plan                                                                                                                   57       

4.7.2 Testing Data                                                                                                                   58       

4.7.3 Actual Test Result versus Expected Test Result                                                           58

4.7.4 Performance Evaluation                                                                                                 59

4.7.5 Limitation of the System                                                                                               59       

4.8 System Conversion                                                                                                           60       

4.8.1 Changeover Procedure                                                                                                   60       

4.8.2 Recommended Procedure                                                                                              61       

4.9 System Security                                                                                                                61       

4.10 Documentation                                                                                                               61       

4.11 Project Costing                                                                                                               62       

 

CHAPTER 5: SUMMARY, RECOMMENDATION, AND CONCLUSION

5.1 Summary                                                                                                                           64       

5.2 Recommendation                                                                                                              64       

5.3 Conclusion                                                                                                                        65

REFRENCES

APPENDIX I

 

 

 

 

 

 

 

 

 

 

 

 

LIST OF TABLES

Table 1: of Literature Review                                                                                                 22

Table 2: Physical Structure of the New System Database                                                      45

Table 3: Information Stored in New System Database                                                          46

Table 4: Data Dictionary of New System                                                                               51

Table 5: Result Table using Test data.                                                                                    58

Table 6: General project Cost.                                                                                     63

 

 

 

 

 

 

 

 

 

 

 

LIST OF FIGURES

Figure 1: Face Recognition Sample                                                                                        3

Figure 2: Face Recognition Processing                                                                                   16

Figure 3 Face Recognition Operation                                                                                     19

Figure 4: Proposed System Authentication Process                                                               27

Figure 5: The Research Method used for Implementation                                                     30

Figure 6: Component of the New System                                                                              36

Figure 7: Main Menu of New System                                                                                    42

Figure 8: Physical Design of the New System Database                                                        44

Figure 9: account holder registration                                                                                      48

Figure 10: Biometricregistration                                                                                             48

Figure 11: Output Format of the New System                                                                       49

Figure 12: Use case diagram of the New System                                                                   50

Figure 13: Program flowchart of New System                                                                       54

Figure 14: The Complete System Architecture                                                                       55

 

 

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APA

AKOMA, P (2024). Face Recognition And Qrcode Attendance Taken And Verification System Using Deep Learning Approach:-Akoma, Knowledge P.. Repository.mouau.edu.ng: Retrieved Nov 21, 2024, from https://repository.mouau.edu.ng/work/view/face-recognition-and-qrcode-attendance-taken-and-verification-system-using-deep-learning-approach-akoma-knowledge-p-7-2

MLA 8th

PAUL, AKOMA. "Face Recognition And Qrcode Attendance Taken And Verification System Using Deep Learning Approach:-Akoma, Knowledge P." Repository.mouau.edu.ng. Repository.mouau.edu.ng, 10 Jan. 2024, https://repository.mouau.edu.ng/work/view/face-recognition-and-qrcode-attendance-taken-and-verification-system-using-deep-learning-approach-akoma-knowledge-p-7-2. Accessed 21 Nov. 2024.

MLA7

PAUL, AKOMA. "Face Recognition And Qrcode Attendance Taken And Verification System Using Deep Learning Approach:-Akoma, Knowledge P.". Repository.mouau.edu.ng, Repository.mouau.edu.ng, 10 Jan. 2024. Web. 21 Nov. 2024. < https://repository.mouau.edu.ng/work/view/face-recognition-and-qrcode-attendance-taken-and-verification-system-using-deep-learning-approach-akoma-knowledge-p-7-2 >.

Chicago

PAUL, AKOMA. "Face Recognition And Qrcode Attendance Taken And Verification System Using Deep Learning Approach:-Akoma, Knowledge P." Repository.mouau.edu.ng (2024). Accessed 21 Nov. 2024. https://repository.mouau.edu.ng/work/view/face-recognition-and-qrcode-attendance-taken-and-verification-system-using-deep-learning-approach-akoma-knowledge-p-7-2

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