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License Plate Recognition

Visionaire License Plate Recognition (Docker Stream) is a containerized Artificial Intelligence Analytics which provides recognition of license plates for all types of vehicles. Nodeflux LPR is using a Deep Learning algorithm developed to adapt to real conditions in Indonesia, like various kinds of plates, and any wide range of environmental conditions.
How it Works
License Plate Recognition Analytic
Deployment Schema
Analytics Performance
LPRv2
Parameter
Value
Character Accuracy
98.71%
Plate Type
Military, Police, Diplomat, Public (Only Indonesia)
Weather Condition
Rainy, Dusty, Visible Low-Light, Daylight
Minimum Plate Size
250px x 150px 
Maximum Tilt
30°
Plate Condition 
Bended, Cropped, Framed
LPR-S (Special Case)
Parameter
Value
Character Accuracy
80%
Plate Type
Indonesian Military (TNI AD, AL, AU), Mabes TNI, Police, Private
Weather Condition
Rainy, Dusty, Visible Low-Light, Daylight
Minimum Plate Size
250px x 150px 
Maximum Tilt
30°
Plate Condition 
Bended, Cropped, Framed

Parameter	Value
Character Accuracy	98.71%
Plate Type	Military, Police, Diplomat, Public (Only Indonesia)
Weather Condition	Rainy, Dusty, Visible Low-Light, Daylight
Minimum Plate Size	250px x 150px
Maximum Tilt	30°
Plate Condition	Bended, Cropped, Framed

Parameter	Value
Character Accuracy	80%
Plate Type	Indonesian Military (TNI AD, AL, AU), Mabes TNI, Police, Private
Weather Condition	Rainy, Dusty, Visible Low-Light, Daylight
Minimum Plate Size	250px x 150px
Maximum Tilt	30°
Plate Condition	Bended, Cropped, Framed

Testing

Camera Guideline

Last modified 25d ago