License plate detection and recognition using Artificial Intelligence

One of our clients was facing difficulties in timely reporting license plates of its site visitors to the local municipality. The local city council required our client to timely report on a list of vehicles for visitors to its site, as the parking space needed to be accounted for by the city’s administration.

This was quite a manual chore, as an office employee would have to go outside, take note of the different license plates, sometimes over 200 at a time. The process was prone to a lot of errors and irregularities, making it difficult for our client to meet the city council’s standards, which resulted in fines for our client.

For this client, we built a web application powered by machine learning models to automatically detect and recognize license plates. The detection and recognition algorithms even work on international license plates, namely all European license plates formats.

General idea of the web application which we developed for our client

Using the web application, an office employee could take a casual stroll across the parking site, taking pictures or a video with her smartphone along the way. She would then upload the pictures from our smartphone to our web application, validate the results and immediately send a report to the city council, with a carbon copy e-mail for herself for future reference.

Thanks to this solution, our client was able to timely and accurately report the license plates of its visitors to the city council.

In addition, we connected the recordings of the license plates to our client’s Business Intelligence solution, allowing our client to infer analytics on returning visitors by car.

Would you like to learn more about our license plate recognition algorithms, or about our automation solutions in general? Contact us at hello@oakwood.ai.

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By | 2019-04-01T17:43:59+01:00 April 1st, 2019|Categories: Automation, Computer Vision, Machine Learning, Use cases|0 Comments

About the Author:

Koen is co-founder of Oakwood and specializes in Artificial Intelligence, Machine Learning and Natural Language Processing. He's highly proficient with Python and NodeJS.

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