At a glance
- Recognition Speed
- Face under 100 ms, palm under 140 ms
- Interface
- USB 2.0
- Dimensions
- 80.0 × 40.0 × 26.0 mm
- Palm Recognition Distance
- 18 to 40 cm
- Power Supply
- 5 V DC, 2.0 A
Armatura AMT-FAPVR-30 Face and Palm Recognition Reader, Dual-Lens, USB
₹45,885 Incl. GST
₹38,886 + 18% GST
At a glance
- Recognition Speed
- Face under 100 ms, palm under 140 ms
- Interface
- USB 2.0
- Dimensions
- 80.0 × 40.0 × 26.0 mm
- Palm Recognition Distance
- 18 to 40 cm
- Power Supply
- 5 V DC, 2.0 A
Ready-housed USB reader that recognises faces and palms, for enrolment desks, visitor counters, bank counters and point-of-sale PCs. Stores 30,000 faces and 5,000 palms, reads faces at 40 to 120 cm and palms at 18 to 40 cm, with liveness detection.
- WarrantyManufacturer warranty under Armatura's terms. Warranty claims
- DeliveryPrice, availability and delivery charges are confirmed in your quotation. Shipping and delivery
Overview
The Armatura AMT-FAPVR-30 is a ready-housed USB reader that recognises faces and palms, for enrolment desks, visitor counters, bank counters and point-of-sale PCs. It pairs a visible light camera with an infrared camera and runs the recognition on its own processor and neural processing unit (NPU), so matching happens on the device and the PC simply receives the result over USB.
It is a component for developers and system builders to integrate into their own software, not a door terminal.
Is it right for you?
- Suits a software team building a desktop enrolment station, visitor desk or counter application that needs biometric identification from a PC.
- Not a door controller. For a ready to fit door terminal, see the Armatura OmniAC series.
- Integration needs software written with Armatura’s MultiBio SDK for Windows or Android.
Key features
- Face and palm recognition in one unit, with liveness detection on both to resist photos and replicas.
- Stores up to 30,000 faces and 5,000 palms on the module, for 1:1 or 1:N matching.
- Face matching in under 100 ms at 40 to 120 cm; palm matching in under 140 ms at 18 to 40 cm.
- Face accuracy of TAR 99% at FAR 0.01%; palm accuracy of TAR 98.7% at FAR 0.01%.
- Face mask detection, and age, gender and expression attributes.
- 2 MP visible light camera (1/2.8 inch HDR CMOS, 106 dB dynamic range) and 1.3 MP infrared camera (1/4 inch CMOS, global shutter), at 15 frames per second, with a 60 degree horizontal field of view.
- 1.2 GHz quad-core ARM processor with a 2.4 TOPS NPU, 1 GB RAM and 512 MB flash.
- USB 2.0 with UVC and HID protocols, powered at 5 V DC, 2 A; under 2.5 W on standby and under 3.5 W in operation.
- 80 x 40 x 26 mm; works from -10 to 55 °C at 15 to 95% humidity; CE, FCC and RoHS certified.
What else you need
A host device (PC, kiosk computer or Android board) with a USB 2.0 port, and software built on the Armatura MultiBio SDK.
Installation
This is a component for integration by a software or engineering team rather than an installer. Position it where the face is 40 to 120 cm away, or the palm 18 to 40 cm away, in lighting from 0.01 lux upwards.
Software and licences
Needs application software written with the Armatura MultiBio SDK for Windows or Android.
Before you buy
- The minimum order is 200 pieces.
Technical specifications
Key facts
- What is it?
- Enrollment deviceBrand Armatura
- How is it powered?
- 5 V DC
- Which documents are available?
- Datasheet, online specifications, software Open documents
- Can SecurityGearHub help with installation?
- Setup guidanceManuals, wiring guides and answers to setup questions. On-site work is arranged separately where available. Ask about installation
- Not stated by the manufacturer
- PoE, RS-485, OSDP, wiegand, outdoor rating, box contents
General
- Model / configuration
- AMT-FAPVR-30
- Configuration
- Visible Light Facial and Palm Recognition Reader
embedded Facelite and Palmlite SDK - Processor
- 1.2 GHz quad-core ARM, 2.4 TOPS NPU
- Memory
- 1 GB RAM + 512 MB Flash
- Cameras
- 2.0 MP visible light (1/2.8 in HDR CMOS) and 1.3 MP infrared (1/4 in CMOS, global shutter)
- Interface
- USB 2.0
- Protocol
- UVC and HID
- Face Recognition Distance
- 40 to 120 cm
- Palm Recognition Distance
- 18 to 40 cm
- Accuracy
- Face TAR 99% at FAR 0.01%; palm TAR 98.7% at FAR 0.01%
- Recognition Speed
- Face under 100 ms; palm under 140 ms
- On-Module Capacity
- 30,000 faces; 5,000 palms
- Liveness Detection
- Face: infrared plus visible, or infrared; palm: infrared
- Field of View
- 60° horizontal, 36° vertical, 67° diagonal
Input
- Power Supply
- 5 V DC, 2.0 A
- Power Consumption
- Under 2.5 W standby; under 3.5 W operating
Environment
- Operating Temperature
- -10 °C to +55 °C
- Operating Humidity
- 15 to 95% RH
Physical
- Dimensions
- 80.0 × 40.0 × 26.0 mm
Approvals
- Certifications
- CE, FCC, RoHS
- Warranty
- Manufacturer warranty under Armatura's terms. How claims work
Product attributes and shipping details
| Brand | Armatura |
|---|
Downloads
Download software
- Armatura product pageWindows and Android (PalmMobile also iOS)Prerequisites: Developer integration; Module needs SDK integration; SDK package via Armatura salesLicence: Free; account requiredSoftware · Family · armatura.usView official download page
Documentation
- Armatura AMT-FAPVR-30 datasheetDatasheet · This model · d1agmp9y4cki1i.cloudfront.netDownload
- Armatura AMT-FAPVR-30 product pageOnline specifications · This model · zkteco.inView official page
Series documents can differ from your exact model. Report a wrong or missing file
Questions about this product
Is this a door access terminal?
No. It is a USB reader for developers and system builders to integrate into their own PC or Android applications.
How many faces and palms can it store?
Up to 30,000 faces and 5,000 palms on the module.
What software do I need?
Application software built with the Armatura MultiBio SDK for Windows or Android.
What power does it need?
5 V DC at 2 A over USB 2.0, drawing under 3.5 W in operation.
Does it work in low light?
The visible light camera works from 0.01 to 50,000 lux and the infrared camera from 0.01 to 20,000 lux.
What is the minimum order?
200 pieces.
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