Recognising license plate from image data using deep learning

This thesis is submitted in partial fulfillment of the requirements for the degree of Bachelor of Science in Computer Science and Engineering, 2022.

Sonraí bibleagrafaíochta
Príomhchruthaitheoirí: Golder, Rupam, Rahman, Sadman, Shams, MD. Isteak, Hasan, Jawad, Bakhtiar, Fahim Muhammad
Rannpháirtithe: Anwar, MD. Tawhid
Formáid: Tráchtas
Teanga:English
Foilsithe / Cruthaithe: Brac University 2023
Ábhair:
Rochtain ar líne:http://hdl.handle.net/10361/21804
id 10361-21804
record_format dspace
spelling 10361-218042023-10-15T21:05:06Z Recognising license plate from image data using deep learning Golder, Rupam Rahman, Sadman Shams, MD. Isteak Hasan, Jawad Bakhtiar, Fahim Muhammad Anwar, MD. Tawhid Rahman, Rafeed Department of Computer Science and Engineering, Brac University License plate EasyOCR YOLOv5 YOLOv7 Deep learning (Machine learning) Optical character recognition devices This thesis is submitted in partial fulfillment of the requirements for the degree of Bachelor of Science in Computer Science and Engineering, 2022. Cataloged from PDF version of thesis. Includes bibliographical references (pages 35-37). Maintaining surveillance and security on the roads has become a significant challenge, which is why it has become necessary to conduct proper methods to control this problem. To ensure security and safety on the roads, methods such as Automatic Number Plate Recognition is implemented so that all crimes and other security-related issues may scale down. In this paper, two versions of YOLO are used. The first one is YOLOv5, and afterward, the most recent model of YOLO, which is YOLOv7. These models are used so that we may get better results com- pared to all other previously used models. Eventually, EasyOCR is used to extract the characters from the number plate. The proposed models are tested on the LP dataset, our custom dataset consisting of 10,700 images. 93.8% and 95.6% accuracy are acquired from YOLOv5 and YOLOv7, respectively. However, the main goal of this research paper is to prove that YOLO is superior to other models in terms of object detection. In addition, YOLOv7 provides us with improved results compared to YOLOv5. Rupam Golder Sadman Rahman MD. Isteak Shams Jawad Hasan Fahim Muhammad Bakhtiar B.Sc. in Computer Science 2023-10-15T04:52:42Z 2023-10-15T04:52:42Z ©2022 2022-09-29 Thesis ID 18301040 ID 18301037 ID 18301228 ID 18301242 ID 18301095 http://hdl.handle.net/10361/21804 en Brac University theses are protected by copyright. They may be viewed from this source for any purpose, but reproduction or distribution in any format is prohibited without written permission. 50 pages application/pdf Brac University
institution Brac University
collection Institutional Repository
language English
topic License plate
EasyOCR
YOLOv5
YOLOv7
Deep learning (Machine learning)
Optical character recognition devices
spellingShingle License plate
EasyOCR
YOLOv5
YOLOv7
Deep learning (Machine learning)
Optical character recognition devices
Golder, Rupam
Rahman, Sadman
Shams, MD. Isteak
Hasan, Jawad
Bakhtiar, Fahim Muhammad
Recognising license plate from image data using deep learning
description This thesis is submitted in partial fulfillment of the requirements for the degree of Bachelor of Science in Computer Science and Engineering, 2022.
author2 Anwar, MD. Tawhid
author_facet Anwar, MD. Tawhid
Golder, Rupam
Rahman, Sadman
Shams, MD. Isteak
Hasan, Jawad
Bakhtiar, Fahim Muhammad
format Thesis
author Golder, Rupam
Rahman, Sadman
Shams, MD. Isteak
Hasan, Jawad
Bakhtiar, Fahim Muhammad
author_sort Golder, Rupam
title Recognising license plate from image data using deep learning
title_short Recognising license plate from image data using deep learning
title_full Recognising license plate from image data using deep learning
title_fullStr Recognising license plate from image data using deep learning
title_full_unstemmed Recognising license plate from image data using deep learning
title_sort recognising license plate from image data using deep learning
publisher Brac University
publishDate 2023
url http://hdl.handle.net/10361/21804
work_keys_str_mv AT golderrupam recognisinglicenseplatefromimagedatausingdeeplearning
AT rahmansadman recognisinglicenseplatefromimagedatausingdeeplearning
AT shamsmdisteak recognisinglicenseplatefromimagedatausingdeeplearning
AT hasanjawad recognisinglicenseplatefromimagedatausingdeeplearning
AT bakhtiarfahimmuhammad recognisinglicenseplatefromimagedatausingdeeplearning
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