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License Plate Recognition
“How accurate is your LPR system?” This is one of the most common questions we are asked, as well as the most difficult to answer. License plate recognition accuracy is highly dependent on the quality of input video. If a human can’t discern the license plate characters, then the software will also struggle. If the camera was properly set up, high accuracy is likely. Conversely, results may be less accurate if the camera did not clearly capture license plates.
To verify that your camera can work with an LPR system, try performing a test. Freeze a frame as a car drives past and try to read the number plates. If you cannot do this easily, the LPR system will not be successful. Even if the plate numbers are legible, the camera may not be ideally configured for LPR. Human brains are remarkably good at identifying patterns from visual imagery; however, a computer needs a clear, ideal image to perform optimally.
In the image below, the license plate appears to be legible. We can read “B 2506 TIS” The letters, however, are not sharply contrasted. The blurry shades of gray blend into the plate background and other characters. A machine will struggle to accurately read a plate such as this.
The same license plate is much better defined in the following photo, in which the lighting was upgraded and the camera was zoomed in.
The most important factors affecting LPR accuracy are camera placement and video quality. To achieve the highest possible performance for your LPR system, optimize the following variables:
Last modified 8mo ago
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