دورية أكاديمية

Automatic Number Plate Recognition of Saudi License Car Plates

التفاصيل البيبلوغرافية
العنوان: Automatic Number Plate Recognition of Saudi License Car Plates
المؤلفون: R. Antar, S. Alghamdi, J. Alotaibi, M. Alghamdi
المصدر: Engineering, Technology & Applied Science Research, Vol 12, Iss 2 (2022)
بيانات النشر: D. G. Pylarinos, 2022.
سنة النشر: 2022
المجموعة: LCC:Engineering (General). Civil engineering (General)
LCC:Technology (General)
LCC:Information technology
مصطلحات موضوعية: Computer Vision, Edge Detection, Segmentation, OCR, License Plate, Recognition System, Engineering (General). Civil engineering (General), TA1-2040, Technology (General), T1-995, Information technology, T58.5-58.64
الوصف: Automatic license plate recognition has become a significant tool as a result of the development of smart cities. During the experiment studied in the current paper, 50 images were used to detect Saudi car plates. After the preprocessing stage, the canny edge method to detect the car edges and different threshold techniques were used to reduce noise. Horizontal projection was applied in the segmentation process to split the plate. After that, a masking technique was utilized to locate and separate the region of interest in the image. OCR was applied to the processed images to read the characters and numbers in English and Arabic separately. Then, combining the English and Arabic text, after using the re-shaper for the Arabic letters. Finally, rendering of the results of text on images down the plate regions took place. The canny algorithm with projection technique with a proper preprocessing for images produces results with accuracy of 92.4% and 96% for Arabic and English language respectively.
نوع الوثيقة: article
وصف الملف: electronic resource
اللغة: English
تدمد: 2241-4487
1792-8036
Relation: https://etasr.com/index.php/ETASR/article/view/4727; https://doaj.org/toc/2241-4487; https://doaj.org/toc/1792-8036
DOI: 10.48084/etasr.4727
URL الوصول: https://doaj.org/article/742b2683545b46cdb1ce57b3b8c23a9d
رقم الأكسشن: edsdoj.742b2683545b46cdb1ce57b3b8c23a9d
قاعدة البيانات: Directory of Open Access Journals
الوصف
تدمد:22414487
17928036
DOI:10.48084/etasr.4727