Description
·Communication interface : USB and UART
·1:N Identification (One-to-Many)
·1:1 Verification (One-to-One)
·High speed fingerprint identification algorithm engine
·Self study function
·Fingerprint feature data read/write functions
·Get Feature Data of Captured fingerprint and Verify/Identify
Downloaded Feature with Captured
·Fingerprint Identify Downloaded Feature with Captured fingerprint
·Security Level setting
·Able to set BaudRate/ Device ID/Device Password
·Operating system:Windows 98, Me, NT4.0, 2000, XP,WIN 7 or AndroidSpecifications
·Interface:USB 2.0 and UART(3.3V-TTL logic)
·Resolution:508 DPI
·Work Current: <55mA
·Voltage: DC 4.2-6.0V
·Fingerprint capacity:1000
·Security Level: 1-5, default is 3
·Sensor Array: 208*288 pixel
·Fingerprint reader module size: 20.4 * 33.4 (mm)
·Effective collection area: 11 * 15 (mm)
·ScanningSpeed: < 0.2 second
·Verification Speed: < 0.3 second
·Matching Method: 1:1; 1:N
·FRR (False Rejection Ratio): ≤0.01%
·FAR (False Acceptance Ratio): ≤0.00001%
·Work environment: -20°C ---55°C
·Work Humidity: 20-80%
·Communications baud rate (UART): (9600 × N) bps where N = 1 ~
12(default N = 6, ie 57600bps)Files
·All fingerprint module support with Arduino, Android, Windows,
Linux, .Net and so on.
·Provide Free SDK Files
·Provide User ManualHow secure is fingerprint recognition?
Fingerprint recognition has high security, but it is not foolproof.
Its security mainly depends on the following aspects:
1. Difficult to replicate
Fingerprints have uniqueness and stability. Compared to traditional
password and pattern unlocking, fingerprint recognition is more
difficult to forge. On the one hand, fingerprint images need to be
collected through specific sensors, and high-precision replication
requires professional equipment. On the other hand, certain
devices, such as ultrasonic fingerprint sensors, also have the
ability to detect blood flow and live features, further enhancing
safety.
2. Encrypt storage and transmission
In smart devices, fingerprint data is usually not directly stored
as an image, but is converted into feature data through hash
functions or other encryption algorithms and stored in a secure
area of the device (such as Apple's Secure Enclave or Android's
Trust Zone). During each verification, the device compares
real-time fingerprint data with stored feature data. The entire
process adopts end-to-end encryption to ensure that data is not
easily intercepted by hackers.
3. Prevent forgery attacks
Although fingerprint recognition has high security, it is not
unbreakable. For example, early capacitive fingerprint sensors
could be deceived through silicone models or fingerprint imitation.
To cope with this type of attack, current sensor technology is
constantly improving, not only adding live detection capabilities,
but also combining other biometric features (such as facial
recognition, iris scanning) for dual verification, thereby further
enhancing anti-counterfeiting capabilities.
4. Impact of environmental factors
One issue with fingerprint recognition is the impact of the
environment on its recognition accuracy. For example, when the
user's fingers are wet, dry, dirty, or have wounds, the fingerprint
image may not be fully captured, resulting in recognition failure.
In this case, some devices allow users to set multiple fingerprints
to increase the success rate of unlocking.
