How AI and Machine Learning Drive More Accurate Vehicle Recognition
The integration of artificial intelligence and machine learning into license plate/vehicle recognition systems delivers faster and more accurate results.
Traditional optical character recognition software that supports many license plate recognition systems is designed to compare video captures of license plates against a database of stolen/wanted vehicles, but that’s about it. Patrol officers often must manually query the LPR system directly to run an analysis to confirm vehicle characteristics and match compliance, which adds to their workload.
By doing much of the work in the background, a license plate recognition system powered by artificial intelligence can help law enforcement agencies catch more criminals by analyzing video and providing alerts in real time. (Rekor Systems)
In contrast, when LPR systems are integrated with artificial intelligence and machine learning, they can do much more. The AI takes a large workload off law enforcement personnel by working in the background to match captured video/images with known hotlists of stolen vehicles and plates.
Using several analytic algorithms, Rekor Scout compares video/images against plates found in the provided hotlist and any other database the agency specifies – without any human intervention. Whenever a match is found, the system automatically alerts personnel in real time.
HOW ARTIFICIAL INTELLIGENCE PROVIDES BETTER RESULTS, FASTER
With artificial intelligence and machine learning, Rekor Scout moves beyond being a passive database and acts as an active contributor with capabilities based on years of research and testing. This is made possible through neural networks, the data processing system behind artificial intelligence and machine learning.
“Neural networks combine massive amounts of processing power with massive amounts of data, literally training the AI systems to examine the data and infer conclusions from it,” said Matt Hill, chief science officer for Rekor Systems. “This process is known as ‘deep learning,’ and it’s what allows Scout to examine video data and draw conclusions.”
Hill likens the technology to someone sitting by the side of the road watching passing vehicles to see what they can learn about those vehicles by observing them closely. Rekor Scout follows a similar process thanks to deep learning.
“With Scout, we can tell you not only the plate information, but the make, model and color of the vehicle, plus unique identifiers such as bumper damage and stickers,” he said. This is so much more than a conventional LPR system is capable of.”
HOW ARTIFICIAL INTELLIGENCE BENEFITS SECURITY PROFESSIONALS
By doing much of the work in the background, a vehicle recognition system with AI can help security providers and agencies accomplish more without added effort and time.
The Rekor Scout software combs camera footage in the background, only requiring officers’ time when it finds a match. The results are based on the platform’s ability to dynamically analyze video data and then infer conclusions about it. This provides a force multiplier effect, as officers can directly respond without requiring manual surveillance.
The company uses AI and machine learning, based on several years of data and license plate/vehicle images, to increase accuracy and constantly improve results. With the intelligence provided by the system.
“Even though Rekor Scout is state-of-the-art, we are constantly improving it,” said Hill. “For instance, we’ve just added a new feature that can identify a car by a unique sticker or body damage. So even if you can’t see the license plate due to a fuzzy video image, you may still be able to identify the car. That’s the kind of innovation we’re always pursuing at Rekor Systems.”
Visit Rekor Systems for more information.
Portions of the this article originally appeared on Police1 sponsored by Rekor Systems.