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LPR Camera PGS
lannerEye
Ai LPR
LannerEYE is an Artificial Intelligence, deep-learning-based License Plate Recognition (LPR) engine that is more accurate than traditional OCR image processing systems.
A history of innovation and customer satisfaction.
LannerEYE represents a groundbreaking leap in License Plate Recognition (LPR), exclusively relying on 100% deep learning methodologies executed on CPU’s. Departing from conventional OCR engines rooted in image processing, LannerEYE showcases unparalleled adaptability to distortions in license plate images.
Crafted with a series of convolutional neural networks, LannerEYE integrates state-of-the-art activation functions, object recognition-optimized loss functions, and overfit-prevention mechanisms, enhancing both accuracy and reliability.
LannerEYE undergoes extensive training, encompassing millions of real and virtual license plate images, simulating diverse conditions like illumination, angles, and damages. Leveraging advanced data augmentation techniques, virtual images contribute to a comprehensive training dataset.
Efficiency is at the forefront, as LannerEYE is exclusively built in 100% C++ language, enabling swift operation even in the absence of GPU support.
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Demonstrating remarkable proficiency, LannerEYE excels in recognizing license plates under abnormal conditions—angled, damaged, irregular, and light-reflected plates—validated through successful implementations in South Korea and the Philippines.
The machine learning process empowers LannerEYE to adapt to various international license plate formats through comprehensive training, achieving an accuracy rate that continually improves, ultimately aiming for a 100% success rate.
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LannerEYE’s pivotal role extends to essential applications such as Parking Access and Revenue Control Systems (PARCS) and Camera-based Parking Guidance Systems (PGS). In Korea, the recognition rate stands impressively at 99.9%, encompassing diverse license plate types, including those for electric vehicles.
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