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Low-load and high-precision license plate recognition software utilizing AI technology, which supports not only cameras on general roads but also security management and improvement of customer satisfaction in various fields such as parking lots, factories, offices, hospitals, hotels, public facilities, financial institutions and retail stores.
Example of application: License plate detection
- Highly precise license plate recognition
- Being equipped with a recognition engine utilizing AI technology makes it possible to read vehicle numbers with high precision.
- Recognition Precision
- 95% or more
- Recognition Speed
- 38ms (*Measured by DMP's AI FPGA module ZIA™ C3)
- Operable on edge devices
- 1/100 lower load than software OCR technology.
Provision in source code makes it possible to implement in customer's target edge devices such as CPUs, GPUs, or DMP's AI processor ZIA™ DV720)
- Applicable to various applications
- ZIA™ Plate supports security management and customer satisfaction in various fields such as factories, offices, hospitals, hotels, public facilities, financial institutions, and retail stores in addition to roadside cameras.
- Possible to recognize special plates and various countries plates
- Possible to recognize special license plates and various countries license plates
By utilizing AI, it can recognize license plates with designs such as Mt. Fuji or Olympics. It also supports overseas license plates recognition by learning images.
License plate color tone (density)
- The density of a license plate can be detected. Frame color detection is not supported.
- Size (large format / medium format) detection is not supported.
Correspondence to land transportation offices
- Corresponds to the names of the regions started in 2020 such as Shiretoko, Tomakomai, and Hirosaki.
- One-character display (older version) is not supported.
Vehicle classification number
- Compatible with numbers and A, B, C, E, F, H, K, L, M, P, T, X and Y
Vehicle model classification
- Compatible with hiraganas except お, し, へ, ゐ, ゑ and ん and A, B, C, E, F, H, K, L, M, P, T, X and Y
Depression angle: within ±30°, Rotation angle(Horizontal angle): within ±30°, Approach angle: within ±30°
Land transportation offices: 97%,Vehicle classification number: 98%, Vehicle model classification: 97%, Vehicle number: 99%
Recommended Usage Environment
|On-premises / Cloud||
|1. Software Evaluation||
|2. Re-Training of Trained Model||
|3. Software Implementation
|4. Operation / Maintenance||