Automatic License Number Plate Recognition

By Error404 (Bianca Ștefănescu, Alex Silaghi, Cătălin Vanciu)

    Automatic recognition of car license number plate became a very important aspect in our daily life because of the unlimited increase of cars and transportation systems which make it impossible to be fully managed and monitored by humans, examples are so many like traffic monitoring, tracking stolen cars, managing parking toll, red-light violation enforcement, border and customs checkpoints. Yet it’s a very challenging problem, due to the diversity of plate formats, different scales, rotations and non-uniform illumination conditions during image acquisition.

    Most of the number plate detection algorithms fall in more than one category based on different techniques. To detect vehicle number plate following factors should be considered: 

• Plate size: a plate can be of different size in a vehicle image. 
• Plate location: a plate can be located anywhere in the vehicle. 
• Plate background: a plate can have different background colors based on vehicle type. For example a government vehicle number plate might have different background than other public vehicles. 
• Screw: a plate may have screw and that could be considered as a character. 

    A number plate can be extracted by using image segmentation method. There are numerous image segmentation methods available in various literatures. In most of the methods image binarization is used. Some authors use Otsu’s method for image binarization to convert color image to gray scale image. Some plate segmentation algorithms are based on color segmentation.

    In principle, image should first be processed, then Gaussian Blur, Sobel and morphological operations applied. In the end, the only thing left to do should be to extract the text using "pytesseract" and recognize the numbers and characters of the number plate.

    Bibliography:

• Chirag Patel, Dipti Shah, PhD., Atul Patel, PhD. - "International Journal of Computer Applications (0975 – 8887) Volume 69– No.9, May 2013" 
• Amr Badr, Mohamed M. Abdelwahab, Ahmed M. Thabet, and Ahmed M. Abdelsadek - "Annals of the University of Craiova, Mathematics and Computer Science Series Volume 38(1), 2011"
• Xifan Shi, Weizhong Zhao, and Yonghang Shen - "Automatic License Plate Recognition System Based on Color Image Processing