Labeling Service Case Study— Video Annotation — Vehicle License Plate Recognition

--

Vehicle License Plate Recognition

Driven by the continuous innovation of “Ai + IoT” technology and application, a construction boom of “smart city” has been rising all over the world. As a key part of the construction, the intelligent transportation industry has been into the stage of rapid expansion.

Netvision Telecom is a technology company, located in South Korea, specializing in communication and network development. At present, the company undertakes the project of intelligent license plate recognition system of Incheon government in South Korea.

Vehicle license plate recognition (VLPR) is an application of computer video image recognition technology in vehicle license plate recognition. License plate recognition technology requires that the moving license plate can be extracted and recognized from the complex background. Through license plate extraction, image preprocessing, feature extraction, license plate character recognition and other technologies, information such as vehicle number and color can be recognized.

Video Annotation Case Study

To build such a system, firstly, it is necessary to have a large number of car license plate training data, clearly identifying and marking the plate type, background color, text, and number. Then, the recognition algorithm should be continuously trained with labeled pictures to improve the performance.

A Korean Telecom company chose to cooperate with ByteBridge to complete license plate number labeling projects.

ByteBridge firstly disassembles the complex tasks and divides them into several simple components, such as license plate counting, license plate labeling, unlabeled license plate counting, etc. Each part is aligned to a certain consensus mechanism to ensure accuracy.

Single Frame Labeling: The videos are segregated into thousands of images and annotators label them one by one.

Kim, head of the recognition program said, “it’s difficult to complete video annotation cases. The license plate is very small, and there is a lot to do. I didn’t expect that ByteBridge delivered the project in a very short time, with high accuracy and consistency. The overall rate reached 99%, which helped us solve a big problem.”

End

Outsource your data labeling tasks to ByteBridge, you can get the high-quality ML training datasets cheaper and faster!

  • Free Trial Without Credit Card: you can get your sample result in a fast turnaround, check the output, and give feedback directly to our project manager.
  • 100% Human Validated
  • Transparent & Standard Pricing: clear pricing is available(labor cost included)

Why not have a try?

Relevant Articles:

1How Data Labeling Service Empower Auto-Driving Industry2021?

2 How Auto-Driving Achieved through Machine Learning?

3 High-Quality Training Data for Autonomous Cars in 2021

4 What is Semantic Segmentation, Instance Segmentation, Panoramic segmentation?

5 How Data Labeling and Annotation Services Empower Self-Driving Bus?

--

--