License plate recognition
This thesis is submitted in partial fulfillment of the requirements for the degree of Bachelor of Science in Computer Science, 2023.
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Brac University
2023
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| Acesso em linha: | http://hdl.handle.net/10361/21999 |
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10361-219992023-12-18T21:02:34Z License plate recognition Chowdhury, Mohammed Abrar Ahasan Rozaik, Soyelim Al Shanto, Mahedi Hasan Rasel, Annajiat Alim Jahan, Sifat E Department of Computer Science and Engineering, Brac University License plate recognition Tensorflow OCR OpenCV EasyOCR Computer algorithms Artificial intelligence Optical character recognition devices This thesis is submitted in partial fulfillment of the requirements for the degree of Bachelor of Science in Computer Science, 2023. Cataloged from PDF version of thesis. Includes bibliographical references (pages 32-34). In today’s ever-growing technological society, Automatic License plate Recognition, ALPR, has many implications for solving traffic-related applications and transporta- tion planning. Identifying cars in pursuit or stolen cars, controlling automatic park- ing access, registering missing vehicles from last found footage, and in many more hazardous or unpredictable situations, ALPR helps to identify and extract license plate information from surveillance footage. Thus in improving and making ALPR efficient, many techniques have been introduced with algorithms playing an essential part for vehicle surveillance systems, although many challenges are seen in correctly computing and recognizing license plates under different environmental conditions. In this research, we work with different algorithms for understanding Bangladeshi license plates, analyze the algorithms’ efficiency in various environmental conditions or unlikely situations, and compare them with our model, which currently is giving 97% accuracy, to find the most suitable for recognizing them. Mohammed Abrar Ahasan Chowdhury Soyelim Al Rozaik Mahedi Hasan Shanto B.Sc. in Computer Science and Engineering 2023-12-18T04:28:19Z 2023-12-18T04:28:19Z 2023 2023-05 Thesis ID 23141055 ID 23141056 ID 18301185 http://hdl.handle.net/10361/21999 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. 34 pages application/pdf Brac University |
| institution |
Brac University |
| collection |
Institutional Repository |
| language |
English |
| topic |
License plate recognition Tensorflow OCR OpenCV EasyOCR Computer algorithms Artificial intelligence Optical character recognition devices |
| spellingShingle |
License plate recognition Tensorflow OCR OpenCV EasyOCR Computer algorithms Artificial intelligence Optical character recognition devices Chowdhury, Mohammed Abrar Ahasan Rozaik, Soyelim Al Shanto, Mahedi Hasan License plate recognition |
| description |
This thesis is submitted in partial fulfillment of the requirements for the degree of Bachelor of Science in Computer Science, 2023. |
| author2 |
Rasel, Annajiat Alim |
| author_facet |
Rasel, Annajiat Alim Chowdhury, Mohammed Abrar Ahasan Rozaik, Soyelim Al Shanto, Mahedi Hasan |
| format |
Thesis |
| author |
Chowdhury, Mohammed Abrar Ahasan Rozaik, Soyelim Al Shanto, Mahedi Hasan |
| author_sort |
Chowdhury, Mohammed Abrar Ahasan |
| title |
License plate recognition |
| title_short |
License plate recognition |
| title_full |
License plate recognition |
| title_fullStr |
License plate recognition |
| title_full_unstemmed |
License plate recognition |
| title_sort |
license plate recognition |
| publisher |
Brac University |
| publishDate |
2023 |
| url |
http://hdl.handle.net/10361/21999 |
| work_keys_str_mv |
AT chowdhurymohammedabrarahasan licenseplaterecognition AT rozaiksoyelimal licenseplaterecognition AT shantomahedihasan licenseplaterecognition |
| _version_ |
1814307295414190080 |