A Deep Learning Based Approach for Localization and Recognition of Pakistani Vehicle License Plates.

Journal: Sensors (Basel, Switzerland)
Published Date:

Abstract

License plate localization is the process of finding the license plate area and drawing a bounding box around it, while recognition is the process of identifying the text within the bounding box. The current state-of-the-art license plate localization and recognition approaches require license plates of standard size, style, fonts, and colors. Unfortunately, in Pakistan, license plates are non-standard and vary in terms of the characteristics mentioned above. This paper presents a deep-learning-based approach to localize and recognize Pakistani license plates with non-uniform and non-standardized sizes, fonts, and styles. We developed a new Pakistani license plate dataset (PLPD) to train and evaluate the proposed model. We conducted extensive experiments to compare the accuracy of the proposed approach with existing techniques. The results show that the proposed method outperformed the other methods to localize and recognize non-standard license plates.

Authors

  • Umair Yousaf
    Department of Software Engineering, University of Sialkot, Sialkot 51040, Pakistan.
  • Ahmad Khan
    Department of Computer Science, COMSATS University Islamabad, Abbottabad Campus, Abbottabad, Pakistan.
  • Hazrat Ali
    College of Science and Engineering, Hamad Bin Khalifa University, Doha, Qatar.
  • Fiaz Gul Khan
    Department of Computer Science COMSATS Institute of IT, Abbottabad 22060, Pakistan. sajidshah@ciit.net.pk.
  • Zia Ur Rehman
    Department of Physiology, University of Veterinary and Animal Sciences, Lahore, Pakistan.
  • Sajid Shah
    College of Computer and Information Sciences, Prince Sultan University, Riyadh, Saudi Arabia.
  • Farman Ali
    Department of Computer Science, Abdul Wali Khan University Mardan, Pakistan.
  • Sangheon Pack
    School of Electrical Engineering, Korea University, Seoul 02841, Korea.
  • Safdar Ali
    Department of Software Engineering, University of Lahore, Lahore 54000, Pakistan.