AI Binocular Face, Palm Vein & QR Code Recognition Sensor

Q: What must be done when the sensor is in use?

The sensor USB port must be connected to a 5V USB power supply

Q: Can the foam on both sides of the camera be removed?

No, the foam on both sides of the camera cannot be removed

The article offers a detailed guide on installing AI vision modules, focusing on optimal installation heights, recommended tilt angles, cover plate materials, and proper assembly to prevent imaging issues and enhance performance.

2. Example Code for Arduino-Registering Face & Palm Print

When registering face or palm print, you need to fix the AI visual sensor and pay attention to the recognition distance, 30-120cm for face, 15cm for vein palm print, and 15cm for QR code. Only one face or palm print is registered each time. If you need to register multiple, you can press the reset button of the UNO R3 development board to register other faces or palm prints again.

3. Example Code for Arduino-Continuously Recognize Faces, Palm Prints, and QR Codes

Continuously identify faces, palm prints, and QR codes, and print the corresponding information through the serial port monitor. If it cannot be recognized, you can adjust the distance or posture slightly and keep it still.

4. Example Code for Arduino-User Statistics & Deletion

Input command: AT+GETUSERS, query all user numbers and IDs; AT+DELUSER=1, delete the specified user ID1, 1 can be replaced by other user IDs; AT+DELALLUSERS, delete all registered users.

Reference

This article delves into the UART communication protocol and API functions, providing comprehensive instructions for user management, including enrolling and deleting users, as well as enabling recognition through face, palm, and QR code methods. It highlights efficient data management techniques for optimal use.

Specification

Hardware Parameters

Parameter	Details
SoC	Arm CPU@900MHz, [email protected], RISC-V@600MHz
DDR2	64MB
Flash	32MB
Cameras	Dual 1/5” CMOS, 2MP, dual MIPI interfaces
Lens	FOV: 83° diagonal; optimal focus: 60cm
LED	IR@850nm, RGB@650nm (90° illumination)
USB	UVC video transmission (expandable to UAC); MJPEG output (H.264/YUY2 expandable)
Communication	UART@115200 baud

Power Parameters

Parameter	Details
Supply voltage	5-12V
Operating current	320-330mA@8V
Standby current	120–130mA (auto-detection mode)
Shutdown current	0µA (non-auto-detection mode)

Other Parameters

Parameter	Details
Operating temperature	-20°C to +60°C
Storage temperature	-30°C to +70°C
Humidity	10–93% RH (non-condensing)
Audio I/O	Expandable (speaker/microphone)
Boot time	900ms–2.5s (varies with stored user count)
User capacity	1,000 faces; 1,000 palm veins
Algorithms	Binocular liveness detection, deep learning face recognition, palm vein recognition, QR code recognition
Liveness metrics	FAR (False Acceptance Rate) ≤1%; FRR (False Rejection Rate) ≤1%
Face recognition	Pass rate: 98.85%; FAR: 0.001%; Recognition angle: ±20° pitch/yaw; supports multi-angle enrollment
Detection range	Face: 30–120cm，Palm vein/QR code: 15cm
Dimensions	57.8×20×10.12mm

Pinout

UART interface

Pin	Color line sequence	Function description
1	Black line	GND
2	Yellow line	UART_RX
3	Green line	UART_TX
4	Red line	VCC 5~12V

USB interface

Can output video signals for screen display, support standard UVC video, MJPEG/YUY2/H.264 encoding, and have horizontal and vertical screens with multiple resolutions. Can be expanded to realize UAC audio function, can realize voice intercom function.

Pin	Functional Description
1	VCC 5V
2	Floating
3	DM USB data line D-
4	DP USB data line D+
5	GND

Microphone interface (reserved)

Mainly used to receive sound signals and realize intercom function

Pin	Name	Functional Description
1	Negative pole	MIC-
2	Positive pole	MIC+

Speaker interface (reserved)

Mainly used for voice playback

Pin	Name	Functional Description
1	SPK	1W/8Ω
2	SPK	1W/8Ω