License plate recognition system

TECHNOLOGIES NumPy, OpenAlPr, OpenCV, PyCharm, Python
AREAS OF EXPERTISE Image processing, mapping, computer Vision
TEAM 1 developer

A license plate recognition system is among our projects in Computer Vision area. This is a solution for a corporate parking lot. The idea is that the parking lot cameras find the license plates on arriving cars and the gate bar opens for the cars with authorized license plates only.

As the first step of this work, we had to develop a solution which would be able to detect and read the car’s license plates.

  1. The first challenge looks obvious. We need to learn where the license plate is actually located on the car.
  2. The second challenge is that the license plates are different in every country, they have different fonts, the order of letters and numbers, etc. For example, the license plates in Russia have one letter at the beginning, three numbers and then two letters at the end and the area code. The main problem was that most libraries and solutions are built for the foreign countries license plates. So, we had to learn the system to recognize our country license plates as well.
  3. The third challenge was that there could be mistakes in recognition since it can be some sign near the license plate, or any other environment obstacle which could cause the mistake.

To handle these challenges, we used a special library which was strictly focused on license plate recognition. But using that special library was not enough. Our developer had to customize and set it up so that the system would be able to detect a license plate in general and define its combination of letters and numbers.


Currently we have a script which takes a car picture on the input, processes it inside, recognizes the license plate, and, as an output result returns a car picture with marked license plate and its content above. The script provides a high quality of recognition in most cases.

The main advantage of this script is that it can be used in any kind of application, i.e. web, mobile, desktop.

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