ARMATURA AMT-FAPVS-21 User manual

AMT-FAPVS-21 User Manual
P a g e | 1 Copyright© 2022 ARMATURA LLC. All rights reserved.
Thank you for choosing our product. Please read the instructions carefully
before operation. Follow these instructions to ensure that the product is
functioning properly. The images shown in this manual are for illustrative
purposes only.
For further details, please visit our Company’s website
www.armatura.us.
User Manual
AMT-FAPVS-21
Date: October 2022
Doc Version: 1.2
English

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Copyright © 2022 ARMATURA LLC. All rights reserved.
Without the prior written consent of ARMATURA LLC no portion of this manual can be copied or
forwarded in any way or form. All parts of this manual belong to ARMATURA and its subsidiaries
(hereinafter the "Company" or "ARMATURA").
Trademark
is a registered trademark of ARMATURA LLC. Other trademarks involved in this
manual are owned by their respective owners.
Disclaimer
This manual contains information on the operation and maintenance of the ARMATURA product. The
copyright in all the documents, drawings, etc. in relation to the ARMATURA supplied product vests in
and is the property of ARMATURA. The contents hereof should not be used or shared by the receiver
with any third party without express written permission of ARMATURA.
The contents of this manual must be read as a whole before starting the operation and maintenance
of the supplied product. If any of the content(s) of the manual seems unclear or incomplete, please
contact ARMATURA before starting the operation and maintenance of the said product.
It is an essential pre-requisite for the satisfactory operation and maintenance that the operating and
maintenance personnel are fully familiar with the design and that the said personnel have received
thorough training in operating and maintaining the machine/unit/product. It is further essential for the
safe operation of the machine/unit/product that personnel have read, understood, and followed the
safety instructions contained in the manual.
In case of any conflict between terms and conditions of this manual and the contract specifications,
drawings, instruction sheets or any other contract-related documents, the contract
conditions/documents shall prevail. The contract specific conditions/documents shall apply in priority.
ARMATURA offers no warranty, guarantee, or representation regarding the completeness of any
information contained in this manual or any of the amendments made thereto. ARMATURA does not
extend the warranty of any kind, including, without limitation, any warranty of design, merchantability,
or fitness for a particular purpose.

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ARMATURA does not assume responsibility for any errors or omissions in the information or
documents which are referenced by or linked to this manual. The entire risk as to the results and
performance obtained from using the information is assumed by the user.
ARMATURA in no event shall be liable to the user or any third party for any incidental, consequential,
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This manual and the information contained therein may include technical, other inaccuracies, or
typographical errors. ARMATURA periodically changes the information herein which will be
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ARMATURA shall in no way be responsible (i) in case the machine/unit/product malfunctions due to
any non-compliance of the instructions contained in this manual (ii) in case of operation of the
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If there is any issue related to the product, please contact us.
ARMATURA Headquarters
Address 190 Bluegrass Valley Pkwy,
Alpharetta, GA 30005.
For business-related queries, please write to us at [e-mail].
To know more about our global branches, visit www.armatura.us.

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About the Company
ARMATURA is a leading global developer and supplier of biometric solutions which incorporate the
latest advancements in biometric hardware design, algorithm research & software development.
ARMATURA holds numerous patents in the field of biometric recognition technologies. Its products
are primarily used in business applications which require highly secure, accurate and fast user
identification.
ARMATURA biometric hardware and software are incorporated into the product designs of some of
the world’s leading suppliers of workforce management (WFM) terminals, Point-of-Sale (PoS)
terminals, intercoms, electronic safes, metal key lockers, dangerous machinery, and many other
products which heavily rely on correctly verifying & authenticating user’s identity.
About the Manual
This manual introduces the operation of AMT-FAPVS-21.
All figures displayed are for illustration purposes only. Figures in this manual may not be exactly
consistent with the actual products.

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Document Conventions
Conventions used in this manual are listed below:
GUI Conventions
For Software
Convention
Description
Bold font
Used to identify software interface names e.g. OK, Confirm, Cancel.
>
Multi-level menus are separated by these brackets. For example, File > Create >
Folder.
For Device
Convention
Description
< >
Button or key names for devices. For example, press <OK>.
[ ]
Window names, menu items, data table, and field names are inside square
brackets. For example, pop up the [New User] window.
/
Multi-level menus are separated by forwarding slashes. For example,
[File/Create/Folder].
Symbols
Convention
Description
This represents a note that needs to pay more attention to.
The general information which helps in performing the operations faster.
The information which is significant.
Care taken to avoid danger or mistakes.
The statement or event that warns of something or that serves as a
cautionary example.

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Table of Contents
1PRODUCT INTRODUCTION..........................................................................................................7
1.1 OVERVIEW .......................................................................................................................................................7
1.2 FEATURES.........................................................................................................................................................8
2PRODUCT SPECIFICATIONS .........................................................................................................8
2.1 TECHNICAL SPECIFICATIONS............................................................................................................................8
2.2 ELECTRICAL FEATURES.....................................................................................................................................9
2.3 OPTICAL AND IMAGE SPECIFICATIONS ............................................................................................................9
2.4 MODEL SPECIFICATIONS................................................................................................................................ 10
3ALGORITHM SPECIFICATIONS...................................................................................................11
3.1 FACIAL RECOGNITION ALGORITHM................................................................................................................ 11
3.1.1 Face Detection.......................................................................................................................................11
3.1.2 Fake Face Detection ............................................................................................................................12
3.1.3 Mask Detection .....................................................................................................................................13
3.1.4 Facial Attribute Recognition.............................................................................................................13
3.1.5 Facial Recognition................................................................................................................................14
3.1.6 Facial Registration Image Quality Requirements .....................................................................15
3.2 PALM RECOGNITION ALGORITHM................................................................................................................. 16
3.2.1 Palm Recognition Specifications.....................................................................................................17
3.2.2 Palm Registration Image Quality Requirements.......................................................................17
4APPLICATION SCENARIOS .........................................................................................................18
5STRUCTURAL DIMENSIONS.......................................................................................................21
6PORT DEFINITION.......................................................................................................................22
6.1 PORT POSITION AND DEFINITION .................................................................................................................22
6.2 PORT SOCKET DIMENSIONS ..........................................................................................................................22
7CABLE REQUIREMENTS ..............................................................................................................23
8DESIGN GUIDE.............................................................................................................................23
8.1 OPTICAL DESIGN ...........................................................................................................................................23
8.2 HEAT DISSIPATION DESIGN ...........................................................................................................................24
9INSTALLATION GUIDE................................................................................................................25
9.1 INSTALLATION MODES ..................................................................................................................................25
9.2 INSTALLATION HEIGHT AND ANGLE ..............................................................................................................26
9.2.1 Horizontal Installation Mode ...........................................................................................................27
9.2.2 Slant Installation Mode ......................................................................................................................27

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1Product Introduction
1.1 Overview
AMT-FAPVS-21 is a dual-camera multimodal standalone module for face and palm recognition
empowered by high-performance processors. The multimodal standalone module includes
functions such as image collection, biometric template extraction, matching, transmission, and data
management. The module has compact, light-weight size and is highly adaptable to various ambient
lighting and supports touchless multi-biometric recognition.
The dual-camera module is equipped with proprietary ARMATURA facial and palm recognition
algorithms and supports both facial and palm recognition in different application scenarios. The
facial recognition algorithm supports face detection, liveness detection, face mask detection, facial
recognition, age recognition, gender recognition, and facial expression recognition. The palm
recognition algorithm supports palm detection, live palm detection, and palm recognition.
The dual-camera module integrates near-infrared light and support dual-channel image collection
with visible and near-infrared light. Both lenses use low light and wide dynamic range image sensors.
They are excellent in adapting to ambient light with the help of powerful image processing
algorithms. A visible-light lens can capture high quality face images in low illumination (0.01 lux)
and bright light (≤50,000 lux) as well. A near-infrared lens can capture high-resolution, high-
contrast, and distortion-free palm lines and subcutaneous vein images, considerably improving the
recognition accuracy.
The dual-camera module has built-in face and palm algorithms, flexible architecture, and are
suitable for various scenarios. The module provides three application modes for deployment in
different scenarios. They are:
1. The USB video class (UVC) functions as a collection module to stream video.
2. The module does the video streaming and face/palm biometric extraction, while the host does
the biometric comparison.
3. After completion of video streaming, extraction, and biometric comparison in the module. Select
a deployment mode based on application requirements and platform features to make the best
use of dual-camera collection.
The software development interfaces allow quick integration of face and palm recognition functions
to an application platform. The functions apply to areas such as attendance checking, entrance
control, and channel access.

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1.2 Features
•Dual low light and wide dynamic range image sensors, maximum 105 dB dynamic range.
•Supports Face/Palm AE (smart brightness enhancement technologies for facial and palm
recognition).
•Built-in near-infrared light supports smart switch control based on image detection algorithms.
•Captures face and palm images at 25 frames per second
•Maximum face and palm capacities are 100,000 and 10,000.
•Wide field-of-view allows its cameras to recognize individuals at wide varying heights.
•Include SDKs for major platforms (Windows, Android, and Linux).
•Support UVC (USB video device) streaming video protocol and Human Interface Device (HID)
data protocol over USB 2.0.
•Compact, light-weight size with USB 2.0 interface makes for easy integration with a wide range
of host hardware devices
•Provide a touchless, hygienic, and non-invasive biometric identification solution.
•Flexible and open software architecture deployment, adaptable to various application scenarios.
•Integrated communication and power supply USB interface.
2Product Specifications
2.1 Technical Specifications
Features
Technical Specifications
Processor
Quad-core Cortex[email protected] GHz, 1.2 TOPS INT8
Image Sensor
Dual 1/2.8" HDR CMOS, 2MP resolution
(supports visible and near-infrared light)
Communication Interface
USB 2.0
Communications Protocol
Composite UVC device + HID protocol
Camera Type
M8, 2MP

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Required Power Supply
DC 5V/1.1A
Module Size
62 mm x 38 mm x 25.3 mm (Length x Width x
Height)
2.2 Electrical Features
Specifications
Test Conditions
Min
Standard
Max
Unit
Operating Voltage
-
4.75
5.0
5.25
V
Operating Current
T = 25℃, VCC = 5.0
V
-
-
1.1
A
Operating Power
Consumption
T = 25℃, VCC = 5.0
V
-
-
5.5
W
Standby Power
T = 25℃, VCC = 5.0
V
-
-
0.6
A
Standby Power
Consumption
T = 25℃, VCC = 5.0
V
-
-
3
W
Operating Temperature
-
–10
-
45
℃
Storage Temperature
-
–40
-
85
℃
2.3 Optical and Image Specifications
Type
Visible-light Lens
Near-infrared Lens
Resolution @Frame
rate
720 x 1280@25fps
480 x 640@25fps
720 x 1280@25fps
480 x 640@25fps
Default Output
Format
MJPEG
NV12
Signal-to-Noise
Ratio
50 dB
50 dB

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Dynamic Range
105 dB
105 dB
Min Illumination
0.01 lux
0.01 lux
Max Illumination
50,000 lux
20,000 lux
Image Distortion
Rate
≤ 0.5%
≤ 0.5%
Aperture
F2.0
F2.0
Vertical Viewing
Angle
Horizontal Viewing
Angle
2.4 Model Specifications
Model
Features
AMT-FAPVS-21
Supported Algorithm Type
Facial Recognition
Palm Recognition
Effective Image Range
(Algorithm Recognition Range)
50cm - 160cm
(1.5 feet –5 feet)
15cm - 40cm
(6 inch –15 inch)

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3Algorithm Specifications
3.1 Facial Recognition Algorithm
Based on years of in-depth technological development in the biometrics industry, ARMATURA's facial
recognition algorithm is able to handle multi-dimensional face attribute analysis and high-accuracy
face identification from different age groups. It can detect up to 180 face landmark points within
milliseconds, including the landmarks of eyes, lip edges, nose tips, contours and etc. The facial
recognition algorithm supports face detection, liveness detection, face mask detection, age estimation,
gender recognition, facial expression classification, and facial recognition.
The algorithm can detect the face features in a variety of postures. As shown in Figure 3.1 below:
Figure 3.1 Definitions of facial postures
3.1.1 Face Detection
The algorithm can detect and identify a person by human face within a range of 5 feet in a fast and
touchless way.

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Maximum Range
2 m
Detection Speed
25 ms
Min. Image Size
128 x 128 pixels
Static Recognition Ratio
No more than 60% of the whole image
Posture Adaptability
Yaw ≤ 30°, Pitch ≤ 30°, Roll ≤ 45°
3.1.2 Fake Face Detection
The algorithm can distinguish whether the detected face is a real alive face or in a mask or cover
concealing the real identity. It improves the security by prevention from spoofing.
Features
Dual-lens liveness detection (maximum range: 1.6 m or 5
feet)
Visible-light lens detection (maximum range: 2 m or 6.5
feet )
Detection Speed
30 ms
Min. Image Size
128 x 128 pixels
Posture Adaptability
Yaw ≤ 30°, Pitch ≤ 30°, Roll ≤ 45°

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Precision
TAR=99.2% when FAR=0.001%
3.1.3 Mask Detection
The algorithm can detect if a person has worn a mask or not. The feature is very useful to prevent
the epidemic disease and protect the public health.
Function
Detection of masks on faces
Mask Color
Frequently seen masks in White, Black, Blue, Pink, and
Gray
Detection Speed
30 ms
Min. Image Size
128 x 128 pixels
Posture Adaptability
Yaw ≤ 30°, Pitch ≤ 30°, Roll ≤ 45°
Precision
TAR=99.2% when FAR=0.001%
3.1.4 Facial Attribute Recognition
The algorithm is also capable of analyzing and understanding facial attributes such as age, gender,
and facial expression. It can display all the above mentioned attributes when it detects a face, on the
go.

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Facial Attribute Recognition
Age, Gender, and Facial Expression
Facial Expression Types
Calm, Happy, Angry, Sad, Surprised, Afraid, and
Disgusted
Maximum Range
2 m or 6.5 feet
Detection Speed
20 ms
Min. Image Size
128 x 128 pixels
Posture Adaptability
Yaw ≤ 30°, Pitch ≤ 30°, Roll ≤ 45°
Precision
Age recognition (±5 years) > 85%,
Gender recognition > 96%,
Facial expression recognition > 88%
3.1.5 Facial Recognition
The algorithm can detect a face and recognise the identity of the person within fractions of second
and with high accuracy rate.

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Detection Speed
70 ms
Min. Image Size
128 x 128 pixels
Features
1:1, 1:N
Face Capacity
50,000-100,000
Posture Adaptability
Yaw ≤ 30°, Pitch ≤ 30°, Roll ≤ 45°
Precision
TAR=99.2% when FAR=0.001%
3.1.6 Facial Registration Image Quality Requirements
The image saved while face registration has JPG format and the minimum resolution is 128 x 128
pixels. The individual should take care of the following things while registering their face:
•They should not wear a face mask or colored glasses.
•They should ensure that the frame of the glass does not block the eyes and that the
lenses are non-reflective.
•The face angle tolerance for pitch, roll, and yaw should be ±10 degrees.
•The whole face should be in the camera frame and the aspect ratio of the face must not
be distorted.
•Face contours should be clear and the light must be even.
•The facial expression should be natural without obvious exaggeration.

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Figure 3.2 Example of a facial registration image
3.2 Palm Recognition Algorithm
Palm recognition technology is based on near-infrared light to capture palm surface lines and
subcutaneous veins pattern images to identify or verify individual identities. The technology boosts
powerful anti-spoofing functionality because the pattern image is only presented when the fresh
blood is actively flowing through the veins.
AMT PalmLite 12.0 is an excellent near-infrared palm recognition algorithm developed for large-
capacity palm recognition with a high tolerance of palm postures under various lighting conditions.
The algorithm focuses on improving adaptability to an extensive variety of usage environments and
user habits and ensuring high accuracy. In this appoach, the robustness and pass rate are
considerably improved.
The algorithm applies to various palm postures as shown in Figure 3.3:
Figure 3.3 Definitions of palm postures

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3.2.1 Palm Recognition Specifications
Algorithm Version
AMT PalmLite 12.0
Palm Detection Speed
< 50 ms
Biometric Template Extraction
Speed
< 220 ms
Biometric Comparison Speed
< 150 ms
Palm Capacity
6,000-10,000
Posture Adaptability
Yaw ≤ 20°, Pitch ≤ 20°, Roll ≤ 90°, Bend ≤ 15°
Precision
TAR=98.2% when FAR=0.05%
3.2.2 Palm Registration Image Quality Requirements
The image saved while palm registration has JPG or BMP format, and the minimum resolution is 480
x 640 pixels. The individual should take care of the following things while registering their palm:
•The palm and background must be separated.
•The light must be even so that the veins must be visible.
•The whole palm (including the wrist) should be in the camera frame and the aspect ratio
of the palm must not be distorted.
•The palm angle tolerance for pitch, roll, yaw, and bend should be ±5 degrees.

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Figure 3.4 Example of a palm registration image
4Application Scenarios
The AMT-FAPVS-21 dual-camera modules are optimized in structure based on the design and usage
of built-in modules, facilitating quick integration into the host device. Due to the profoundly
integrated design, the dual-camera module can be connected to a platform device using a single USB
cable. In this way, the connection between the power supply and communications device is
accomplished which simplifies the design considerably. The example of an application system is shown
in Figure 4.1 below:

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Figure 4.1 Application system of dual-camera modules
To improve platform adaptability and to lower development difficulty, the dual-camera modules
integrate with all the functions in the biometric recognition application process, including image
collection, image transmission, template extraction, template comparison, template management, and
comparison result output. All the functions can be configured using the software. You can develop a
required application program based on the SDK to achieve your desired functionality and complete
application design.
⚫Image Collection and Transmission
The collection and transmission of the face and palm images are made by a collector. You can
specify different resolutions for image output. For a list of supported resolutions and frame rates,
see section 2.3 Optical and Image Specifications. Image transmission adopts the standard UVC
protocol. Visible and near-infrared light images are transmitted using separate UVC ports. You can
choose the ports as per with image requirements.
⚫Biometric Template Extraction
Biometric template extraction is the most tedious biometric recognition process. To reduce the
impact of the dual-camera modules on platform performance and improve the module's platform
adaptability, the biometric template extraction is performed in the module by default. The high-
performance heterogeneous processor of the dual-camera modules helps free up the computing
resources of your platform.
⚫Template Comparison and Management

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Comparison and management of biometric templates can be performed in the dual-camera
modules or on a platform, according to your requirements.
The modules provide three application modes for use in different scenarios:
1. The UVC functions as a collection module to stream video.
2. The video streaming and face/palm biometric extraction is achieved in the module, while the
biometric comparison is performed by a host.
3. The video streaming, extraction, and biometric comparison are achieved in the module.
If you use the platform for template comparison and management, the module will push the
template to the platform using the Human Interface Devices (HID) port after a biometric template
is extracted. This applies to scenarios in which template storage is strictly restricted. Figure 4.2
shows some functions of a back-end comparison system.
Figure 4.2 Some functions of a back-end comparison system
If you use the module for template comparison and management, the module will only send the
output of the comparison result through the HID port for a client application to call. This can minimize
the computing load of the platform processor. As such, it is particularly suitable for the integration
of the face/palm recognition function in low-performance embedded platforms. Figure 4.3 shows
some functions of a front-end comparison system.