1. Introduction and Overview
The HLK-FM225 and HLK-FM223 are compact facial recognition module solutions primarily designed for integration into various smart devices, such as smart door locks. These modules incorporate a facial algorithm motherboard, binocular cameras (infrared and visible light), and infrared LED lights to perform advanced facial recognition tasks.
The FM225 module utilizes both infrared and visible light cameras to execute functions including face liveness detection, face capture, feature extraction, comparison, and user information storage. Communication is facilitated via UART/USB interfaces, allowing for third-party integration and video transmission. This enables comprehensive face recognition capabilities for smart door locks, with the visible light camera simultaneously providing video images for cat eye visibility functions.
2. Key Features
- Advanced Multi-Modal Live Anti-Counterfeiting: This AI face recognition module offers unparalleled security by effectively blocking attacks from photos, videos, and models, ensuring a 99% pass rate with a false recognition rate of less than one in a million.
- Financial-Grade Liveness Detection: Integrates liveness recognition and vision capabilities, supporting photo distribution functions for enhanced security.
- Seamless Communication: Facilitates communication via UART/USB and supports video transmission to third parties, enhancing functionality for smart door locks and allowing both local and remote video output.
- Deep Learning Dynamic Visible Light Face Recognition: Utilizes a deep learning algorithm with binocular 3D liveness detection for accurate face capture, feature extraction, and user information storage.
- Efficient Design: Features a compact size, low power consumption, and rapid recognition capabilities. It adapts to different lighting conditions, supports varying user heights, and expands recognition angles for improved user experience.
3. Specifications
| Feature | Description |
|---|---|
| Product Name | Face Recognition Module |
| Models | HLK-FM225, HLK-FM223 |
| Communication Interface | UART & USB |
| Face Algorithm | Supports deep learning visible light face recognition algorithm |
| Power Supply Requirements | DC 5.5V-9V @ 1A |
| Working Temperature | -20℃ to +60℃ |
| Storage Temperature | -30℃ to +70℃ |
| Environmental Humidity | 10% - 93% (non-condensing) |
| Application | Computer, Module |
| Package Type | TQFP |
| Dissipation Power | Low |
| Supply Voltage | Standard |
| Condition | New |
| Origin | Mainland China |
| Applicable Scenarios | Smart home, security monitoring, smart door locks, mobile vending machines, and other fields |
4. Setup Instructions
This section outlines the physical connection and basic power-up procedure for the HLK-FM225/FM223 module. For detailed software integration and UART/USB command protocols, please refer to the official developer documentation or SDK provided by the manufacturer.
4.1. Components
- HLK-FM225 or HLK-FM223 Facial Recognition Module
- 4P or 5P connection cable (depending on module variant and required interfaces)
- Compatible power supply (DC 5.5V-9V, 1A)
- Host device (e.g., microcontroller, computer) for communication via UART or USB
4.2. Connection Diagram
Refer to the following diagrams for physical connections. Ensure correct pin assignments to avoid damage to the module or host device.
4.3. Power Connection
- Connect the appropriate power cable to the module's power input.
- Ensure the power supply meets the specified requirements: DC 5.5V-9V at 1A.
- Connect the power supply to a suitable power source.
4.4. Data Communication
- For UART communication, connect the module's UART pins (TX, RX, GND) to your host device's corresponding UART interface.
- For USB communication, connect the module's USB port to your host device using a compatible USB cable.
- Once physical connections are established, proceed with software integration on your host device. This typically involves sending commands and receiving data via the chosen communication interface.
5. Operating Instructions
The HLK-FM225/FM223 module operates by capturing facial data, performing liveness detection, and comparing it against stored user information. The specific operational flow will depend on your application's software implementation.
5.1. Face Enrollment
To enable facial recognition, users must first be enrolled into the module's database. This process typically involves:
- Initiating an enrollment command via UART/USB from the host device.
- The user presenting their face to the module's cameras.
- The module capturing facial features and performing liveness detection to ensure it's a real person.
- Storing the extracted facial features and associated user ID in the module's memory.
5.2. Face Recognition and Liveness Detection
For authentication or identification:
- The module continuously monitors for faces within its field of view.
- Upon detecting a face, it captures images from both visible light and infrared cameras.
- The integrated algorithm performs liveness detection to prevent spoofing attempts (e.g., using photos or videos).
- If liveness is confirmed, the module extracts facial features and compares them against the enrolled database.
- A recognition result (e.g., user ID, match/no match) is then transmitted to the host device via UART/USB.
5.3. Video Output (Cat Eye Function)
The visible light camera can simultaneously output video images, enabling a 'cat eye' function for applications like smart door locks. This video stream can be accessed and processed by the host device for display or recording, depending on the system's design.
6. Maintenance
- Cleaning: Keep the camera lenses and infrared emitters clean and free from dust or smudges. Use a soft, lint-free cloth, possibly dampened with a small amount of lens cleaning solution, to gently wipe the surfaces. Avoid abrasive materials or harsh chemicals.
- Environmental Conditions: Operate and store the module within the specified temperature and humidity ranges (-20℃ to +60℃ operating, -30℃ to +70℃ storage, 10%-93% non-condensing humidity) to ensure optimal performance and longevity.
- Firmware Updates: Periodically check the manufacturer's website for any available firmware updates. Updates can improve performance, add features, or address bugs. Follow the provided instructions carefully when performing updates.
- Physical Inspection: Regularly inspect the module for any signs of physical damage, loose connections, or corrosion. Address any issues promptly.
7. Troubleshooting
7.1. Common Issues and Solutions
| Problem | Possible Cause | Solution |
|---|---|---|
| Module not powering on | Incorrect power supply voltage/current; loose power connection. | Verify power supply meets DC 5.5V-9V @ 1A. Check power cable connections. |
| No communication via UART/USB | Incorrect wiring; incorrect baud rate/port settings; driver issues (for USB). | Double-check UART/USB wiring according to diagrams. Ensure host device communication settings match module. Install necessary USB drivers if applicable. |
| Facial recognition failure or low accuracy | Poor lighting conditions; dirty camera lenses; face not properly positioned; database issues. | Ensure adequate and even lighting. Clean camera lenses. Advise users to position their face clearly within the recognition area. Re-enroll user if necessary. |
| Liveness detection failure | Insufficient IR illumination; user not presenting a live face; environmental interference. | Check IR LED operation. Ensure user is presenting a live face. Minimize strong direct light sources that might interfere with IR. |
7.2. UART Commands and Integration
For detailed information on UART commands and how to configure and integrate the module into your system, please refer to the comprehensive developer documentation or SDK provided by Your Cee. This documentation will contain specific command sets, data formats, and integration guidelines necessary for advanced functionality.
8. User Tips
- Optimal Lighting: While the module adapts to various lighting, consistent and indirect lighting conditions generally yield the best recognition results. Avoid strong backlighting or direct harsh light on the user's face.
- Face Positioning: For reliable recognition, ensure the user's face is centered and fully visible to the module's cameras during enrollment and recognition.
- Software Integration: When integrating with a Windows system or other platforms, ensure your application correctly handles the module's output for user ID verification and data capture. Refer to the SDK for specific API calls and data parsing.
- Regular Cleaning: A quick wipe of the camera lenses with a soft cloth can prevent smudges from affecting performance.
9. Warranty and Support
For warranty information, technical support, and access to the latest documentation and software development kits (SDKs), please contact Your Cee directly or visit their official support channels. Keep your purchase records handy when seeking support.
