Automatic License Plate Detection Solution - Smart City Project
Summary
An industry leader in comprehensive video content analytics platforms based in East Asia sought to enhance its surveillance services to make cities smarter and safer. They approached Folio3 AI to develop an Automatic Number Plate Recognition (ANPR) solution capable of reading vehicle number plates from images, videos, and live camera streams. The solution needed to handle both printed and handwritten number plates in a standard format approved by the authorities and be deployable on-site.
About the Customer
The customer is a prominent company in East Asia specializing in Video Content Analytics Platforms. Their mission is to enhance urban safety and intelligence through advanced surveillance technologies. With a significant market presence and a commitment to innovation, they continuously seek to improve their solutions to meet evolving security needs.
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Team composition
4 members
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Expertise used
Machine Learning, Computer Vision, OCR, ALPR
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Duration
4 months
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Services provided
Model training, Data capture, On-Site Deployment
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Region
Southeast Asia
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Industry
Cyber Intelligence, and Surveillance
Solution
Folio3 AI developed a comprehensive ANPR solution tailored to the client's requirements.
Input Handling
The application could take input from live camera feeds, images, and videos.
Frontend Application
A user-friendly frontend application was developed, allowing users to upload images, and videos, or input live camera feeds.
High Accuracy
Leveraging advanced machine learning algorithms, the solution provided high accuracy in number plate recognition.
User-Friendly Interface
The frontend application allowed users to easily upload and manage input sources.
AI License plate reading
The system was designed to accurately read both printed and handwritten number plates in the standard format.
On-Site Deployment
The solution was designed for on-site deployment, ensuring smooth integration with the client's existing surveillance systems.
Versatility
Capable of processing various input formats, including live camera feeds, static images, and recorded videos.
Robustness
The solution was designed to handle diverse environmental conditions and variations in number plate designs.
Result
With an accuracy above 90%, the successful on-site deployment ensured seamless integration with the client's existing systems, contributing to their mission of making cities smarter and safer.
