1. Product Description
FU460-L face recognition terminal, using RK1109 solution, is a low-cost, highly versatile, and system-stable access control device based on the Linux operating system embedded with Fuge's independently developed binocular 3D liveness detection and neural network deep learning visible light face recognition algorithm. It can be adapted to various types of structures, equipped with a 2 million wide dynamic binocular camera, supports liveness detection and strong backlight environment recognition, with a recognition accuracy of ≥99.9% and a recognition speed of <0.5S, which can achieve extremely fast identity authentication and passage.
My face recognition product is suitable for face recognition access control, attendance machine, face gate, face recognition module and other products.
2. Product Features
● Adopt binocular 3D liveness detection + neural network deep learning visible light face recognition algorithm;
● Support face recognition, card swiping + face combination (optional) verification methods, successful recognition can be displayed in text + voice broadcast;
● Support 8-inch vertical display screen, resolution: 800*1280;
● Support binocular anti-counterfeiting, recognition speed: < 1 second;
● Ultra-wide 145cm~195cm tall and short people adaptability, recognition distance (face) 50~150cm;
● Support all-weather light scene adaptive recognition;
● Standard configuration of 10,000 people, maximum support for 20,000 face databases without error recognition, millisecond recognition speed, no stop passage
● Liveness detection false acceptance rate (LDAFAR): ≤1%;
● Liveness detection false rejection rate (LPFRR): ≤1%;
● Face recognition recognition rate: ≥99.7%, false recognition rate: ≤0.0001%;
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Product model |
FU460-L |
|
SOC |
RV1109 (standard) |
|
DDR4 |
1GB |
|
Flash |
4GB (standard)/8GB |
|
Touch screen |
8-inch IPS LCD 800*1280 (standard without TP) |
|
TP |
Optional |
|
Operating system |
Linux |
|
Face algorithm |
Support standard neural network deep learning visible light face recognition algorithm |
|
Camera |
Binocular (IR+RGB) 200W HD wide dynamic camera |
|
Verification method |
Standard face, card (optional), password |
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Number of users |
Standard 10,000 people (customizable to expand to 2W) |
|
Pass (recognition) rate (face) |
≥99.9% |
|
False recognition rate (face) |
≤0.01% |
|
Recognition angle (face) |
About 20 degrees left and right and up and down |
|
Recognition distance (face) |
50-150CM |
|
Face liveness detection function |
Support |
|
Face liveness detection false acceptance rate (LDAFAR) |
≤1% |
|
Face liveness detection false rejection rate (LPFRR) |
≤1% |
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Network port |
Support TCP/IP (RJ45 interface supports 10M/100M) |
|
WiFi (optional) |
IEEE802.11a/b/g/n |
|
4G (optional) |
7 modes All network access |
|
Second generation ID card reader (optional) |
Support |
|
Card reader (optional) |
IC/ID, NFC, Mifare1 card |
|
Wiegand |
26/34 |
|
USB port |
Support |
|
RS232 |
Support |
|
RS485 |
Support |
|
NC/NO |
Support |
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Power supply |
Default DC12V2A |
|
Anti-bend alarm |
Support |
|
Working temperature |
-20℃~60℃ |
|
Storage temperature |
-30°C ~ 70°C |
|
Relative humidity |
5% ~ 90% RH (non-condensing) |
|
Built-in firmware |
Support access control and attendance system (support report export) |
+86-0755-2607 5207
