How to Use HLK-FM225 Face Recognition Module: Examples, Pinouts, and Specs

The HLK-FM225 is a compact and efficient face recognition module developed by HiLink. It leverages advanced algorithms to detect and recognize human faces with high accuracy and reliability. Designed for real-time processing, the module performs well under various lighting conditions, making it ideal for a wide range of applications.

• Security systems (e.g., surveillance cameras, door locks)
• Access control systems (e.g., office buildings, smart gates)
• Smart home devices (e.g., personalized user authentication)
• Attendance management systems
• Retail and customer analytics

The HLK-FM225 is designed to deliver robust performance while maintaining a compact form factor. Below are its key technical details:

The HLK-FM225 module features a 4-pin interface for easy integration into various systems. Below is the pinout description:

1. Power Supply: Connect the VCC pin to a 5V DC power source and the GND pin to ground.
2. UART Communication: Connect the TX pin of the module to the RX pin of your microcontroller, and the RX pin of the module to the TX pin of your microcontroller.
3. Initialization: Configure the UART communication settings on your microcontroller to match the module's default baud rate (115200 bps). Adjust the baud rate if necessary.

• Ensure the module is placed in a stable position with a clear line of sight to the subject for optimal recognition performance.
• Avoid direct exposure to strong light sources, such as sunlight, to prevent interference.
• Regularly clean the module's lens to maintain accuracy.
• Use a regulated 5V power supply to avoid damage to the module.

Below is an example of how to interface the HLK-FM225 with an Arduino UNO for basic face recognition functionality.

#include <SoftwareSerial.h>

// Define RX and TX pins for SoftwareSerial
SoftwareSerial faceModule(10, 11); // RX = Pin 10, TX = Pin 11

void setup() {
  Serial.begin(9600); // Initialize Serial Monitor
  faceModule.begin(115200); // Initialize HLK-FM225 communication

  Serial.println("HLK-FM225 Face Recognition Module Initialized");
}

void loop() {
  // Check if data is available from the module
  if (faceModule.available()) {
    String data = faceModule.readString(); // Read data from the module
    Serial.println("Data from HLK-FM225: " + data);
  }

  // Send commands to the module (example: enroll a face)
  if (Serial.available()) {
    String command = Serial.readString(); // Read user input from Serial Monitor
    faceModule.println(command); // Send command to the module
  }
}

• Use SoftwareSerial if the Arduino UNO's hardware UART (pins 0 and 1) is already in use.
• Replace 10 and 11 in the SoftwareSerial definition with your preferred pins for RX and TX.

1. No Response from the Module

   • Cause: Incorrect wiring or baud rate mismatch.
   • Solution: Double-check the connections and ensure the UART baud rate matches the module's configuration.

2. Recognition Fails Frequently

   • Cause: Poor lighting conditions or dirty lens.
   • Solution: Improve lighting conditions and clean the lens with a soft cloth.

3. Module Restarts Unexpectedly

   • Cause: Insufficient power supply.
   • Solution: Use a stable and regulated 5V DC power source.

4. Data Corruption in Communication

   • Cause: Long UART cable or electrical noise.
   • Solution: Use shorter cables and ensure proper grounding.

Q1: Can the HLK-FM225 store multiple face templates?
A1: Yes, the module can store up to 500 face templates in its internal memory.

Q2: Can I use the HLK-FM225 outdoors?
A2: While the module operates in a wide temperature range, avoid direct sunlight and extreme weather conditions for optimal performance.

Q3: How do I reset the module to factory settings?
A3: Send the appropriate reset command via UART as specified in the module's command set documentation.

Q4: Is the module compatible with Raspberry Pi?
A4: Yes, the HLK-FM225 can be interfaced with Raspberry Pi using its UART interface.

By following this documentation, users can effectively integrate and utilize the HLK-FM225 Face Recognition Module in their projects.