Đồ án tốt nghiệp - Development of a system for digitalization and information extraction from OD

MINISTRY OF EDUCATION AND TRAINING
HO CHI MINH CITY UNIVERSITY OF TECHNOLOGY AND
EDUCATION
_____________

FACULTY OF MECHANICAL ENGINEERING

SUMMARY GRADUATION THESIS
DEVELOPMENT OF A SYSTEM FOR
DIGITALIZATION AND INFORMATION
EXTRACTION FROM OFFICAL DOCUMENTS
Supervisor:

BUI HA DUC, PhD

Student:

PHAM VU DUNG

Student ID:

19134074

Student:

HOANG PHI HAI

Student ID:

19134076

Year Of Admission:

2019-2023

Ho Chi Minh City, March 2024

Contents
Chapter 1.

Introduction ......................................................... 1

1.1.

Motivation .................................................................... 1

1.2.

Objectives......................................................................... 1

1.3.

System Flow ................................................................. 2

Chapter 2.

Digitalization system ........................................... 3

2.1.

Hardware system........................................................... 3

2.2.

GUI layout.................................................................... 6

Chapter 3.

Information extraction system............................. 7

3.1.

Design document layout analysis algorithm .................... 7

3.2.

Optical Character Recognition ......................................10

3.3.

Design named entity recognition algorithm ....................11

Chapter 4.

Server and Database .......................................... 14

4.1

Architecture .................................................................14

4.2

Server..........................................................................15

4.3

Database......................................................................15

Chapter 5.

Experiment ........................................................ 17

Chapter 6.

CONCLUSION ................................................. 19

INTRODUCTION
Chapter 1.
1.1.

INTRODUCTION

Motivation

Vietnam aims for advanced digital status by 2030, led by Prime
Minister Pham Minh Chinhs vision of digital governance,
economy, and society. The nations swift digital progress is
evidenced by initiatives like the national data sharing platform,
facilitating 1.6 million daily transactions and linking 95% of
civil servant data across ministries. Digitization plays a pivotal
role, converting analog to digital data, streamlining processes,
enhancing security, and cutting costs. Meanwhile, the evolutio n
of NLP and Transformer modules fuels Document AI
...

...
would take a lot of time and not meet our
needs. With the current model—a server connecting to an AI—
we can combine the AI and server on the same computer.
The server here will be a API server because it needs to send
data and images to the GUI. To implement the mentioned
functionalities, each button press will call an API on the server
and perform the corresponding actions.
The server of the project will utilize an HTTP server. Since the
project is not too complex in terms of server issues and requires
quick and flexible development, the Flask library is chosen for
implementation.
4.3

Database

The projects database objective will be online, be to develop
quickly, be expandable, and be free of charge. Leveraging a
NoSQL database in AI projects offers significant advantages by
efficiently managing unstructured data, facilitating horizonta l
scalability for handling large volumes of data, and enhancing
flexibility and performance in data storage, retrieval, and
processing. Based on the analyses provided, Firebase Realtime
Database by Google will be chosen for this project.

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SERVER AND DATABASE
Table 1: Data templates

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EXPERIMENT
Chapter 5.

EXPERIMENT

● Number of testing forms: 14 “anh văn đầu ra” form, 12
“đơn xin thôi học” form, 13 “đơn xin học môn thay thế”
form.
● Result:
-

The percentage of forms that exceed 80% correct
extracted entities rate is 71%.

-

The frequently appeared entities such as name, student
id, etc.. are extracted normally, yet the system sometimes
can not recognize entities like subject id, subject name,
etc. This is because the training data is lacking in the
entities.

Figure 5.1: System result

17

EXPERIMENT

Figure 5.2: System result

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CONCLUSION
Chapter 6.

CONCLUSION

Overall, we can accomplish all the objectives that we proposed.
We designed software that can communicate and control the
scan machine for scanning documents. We can develop deep
learning models that can identify the layout structure of the
document and extract information automatically. The evaluatio n
process suggests that the performance of the system is quite
good.
Nonetheless, our project still has shortages. Firstly, the average
processing time took quite long for a single document file..
Secondly, our project solely focuses on analyzing fill- in forms
in FME faculty, hence it can not be used to analyze other type of
unstructured data without fine-tuning such as birth certificate,
citizen identity card, etc.

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