Automatic Number Plate Recognition of Saudi License Car Plates


  • R. Antar Department of Computer Science, Umm Al-Qura University, Saudi Arabia
  • S. Alghamdi Department of Computer Science, Umm Al-Qura University, Saudi Arabia
  • J. Alotaibi Department of Computer Science, Umm Al-Qura University, Saudi Arabia
  • M. Alghamdi College of Computer and Information Systems, Umm Al Qura University, Saudi Arabia


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.


Computer Vision, Edge Detection, Segmentation, OCR, License Plate, Recognition System


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How to Cite

R. Antar, S. Alghamdi, J. Alotaibi, and M. Alghamdi, “Automatic Number Plate Recognition of Saudi License Car Plates”, Eng. Technol. Appl. Sci. Res., vol. 12, no. 2, pp. 8266–8272, Apr. 2022.


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