Grow R307S Cheap 1000 Capacity USB Uart Optical Fingerprint Module
Certification:CE
Minimum Order Quantity:1
Delivery Time:Peak Season Lead Time: within 15 workdays Off Season Lead Time: within 15 workdays
Payment Terms:T/T, PayPal
Place of Origin:China
Supply Ability:5000
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Location:
Hangzhou Zhejiang China
Address:
Room 310, Building 1-B, No. 279 Shiqiao Road, Xiacheng District, Hangzhou, Zhejiang, China 310012
Supplier`s last login times:
within 28 hours
Product Details
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Product Details
Description
1. Integrated image collecting and algorithm chip together, ALL-in-One2. Fingerprint reader can conduct secondary development, can be embedded into a variety of end products
3. Users can conduct secondary development, can be embedded into a variety of end products, such as: access control, attendance, safety deposit box, car door locks
4. Low power consumption, low cost, small size, excellent performance
5. Professional optical technology, precise module manufacturing technics
6. Good image processing capabilities, can successfully capture image up to resolution 500 dpi
7. Have finger detection function.
8. R307S fingerprint capacity: 1000
Brief description of R307S fingerprint module:
1. Fingerprint capacity:
The storage capacity of R307S fingerprint module is 1000.
2. Description of interface:
R307-S fingerprint module has RS232 and USB2.0 at the same time.USB2.0 interface can connect to the computer;RS232 interface is TTL level, and the default baud rate is 57600, which can be changed. Please refer to the communication protocol.It can be connected with microcontroller, such as ARM, DSP and other equipment with serial port, and the microcontroller of 3.3v and 5V can be connected directly.When connecting to the computer, please pay attention to the level conversion, such as the MAX232 circuit.
3. Module detection
After the fingerprint module is powered on, the fingerprint collection window will flash, indicating that the self-test is normal. If it does not flash, please carefully check the power supply, whether it is connected backwards or wrongly.The chip has some heat when working normally, this is normal phenomenon, the product has passed strict test, can rest assured to use.
Specifications
·Type: Optical·Interface: USB/UART(TTL logical level)
·Resolution: 500 DPI
·Work Current: Typical ≤75 mA
·Voltage: DC 4.2-6.0V (or 3.3V)
·Fingerprint capacity: 1000
·Dimension: 52 *20*22 (mm)
·Image Capture Surface: 15*11 (mm)
·Backlight: Blue
·Sensor Life: 100 million times
·Static Indications: 15KV
·Character file Size: 256 bytes
·Template Size: 512 bytes
·Security Level: 5 (1,2,3,4,5(highest))
·Scanning Speed: < 0.3 second
·Verification Speed: < 0.2 second
·Matching Method: 1:N
·FRR (False Rejection Ratio): ≤0.1%
·FAR (False Acceptance Ratio): ≤0.0001%
·Operating Environment Temperature: -20°C ---50°C
·RS232 communications baud rate: 9600BPS~115200BPS changeable
Files
·All fingerprint module support with Arduino, Android, Windows, Linux, .Net and so on.·Provide Free SDK Files
·Provide User Manual
Progress in Biological Fingerprint Scanning Technology
Biometric fingerprint scanning technology, as an important branch
of biometric recognition, has undergone significant innovation and
progress in recent years. This technology is based on the
uniqueness of individual fingerprints and provides strong support
for fields such as identity verification, security monitoring, and
medical identification through high-precision collection and
analysis.
In the early days, fingerprint scanning mainly relied on
traditional ink pressing methods, which were cumbersome and
inefficient to operate. With the advancement of technology, the
introduction of advanced acquisition technologies such as optics,
capacitance, ultrasound, and biological radio frequency has greatly
improved the accuracy and convenience of fingerprint recognition.
Optical fingerprint scanning captures fingerprint images through
the principle of light reflection, while capacitive technology
utilizes the difference in capacitance between the finger and the
sensor to form fingerprint images. The application of these
technologies not only simplifies the collection process, but also
significantly improves recognition accuracy.
Ultrasonic scanning technology is a major highlight in recent
years. It measures the ultrasonic signals reflected from the
surface of fingerprints to obtain more precise fingerprint depth
information, effectively resisting external factors such as dust
and oil interference. Biological radio frequency technology goes
further by using radio frequency signals to penetrate the dermis
layer of fingers and capture internal features of fingerprints,
adding a new security dimension to fingerprint recognition.
At the algorithmic level, the integration of advanced technologies
such as machine learning and deep learning enables fingerprint
recognition systems to process complex fingerprint images more
intelligently, improving recognition speed and accuracy. These
technologies, through continuous learning and optimization, can
more accurately identify subtle fingerprint features and achieve
efficient verification even under low-quality fingerprint
conditions.
The application of fingerprint recognition technology is
particularly widespread in fields such as financial payments and
security monitoring. In the field of smartphones, the emergence of
under screen fingerprint technology not only increases the screen
to body ratio of devices, but also provides users with a more
seamless identity verification experience. In the payment scenario,
fingerprint recognition has become a standard feature for many
mobile payment platforms and online banks as a fast and secure
means of identity verification. At the same time, the application
in access control systems, attendance management, and monitoring
systems further strengthens security protection and management
efficiency.
However, fingerprint recognition technology also faces some
challenges. Environmental factors such as dust, sweat, and scars
may affect the quality of fingerprints, leading to a decrease in
recognition accuracy. In addition, the threat of fingerprint
forgery cannot be ignored. Although modern technology can
effectively resist most forgery methods, continuous technological
innovation is still the key to ensuring security.
To address these challenges, researchers are working on developing
higher precision collection technologies, such as using
high-resolution sensors to capture subcutaneous fingerprint
structure information and combining artificial intelligence
algorithms to enhance anti-counterfeiting capabilities. At the same
time, the integration of multimodal biometric technology, such as
combining fingerprint recognition with facial recognition, iris
recognition, etc., has also become an important direction for
improving security.
In summary, biological fingerprint scanning technology has made
significant progress in recent years, not only achieving a
qualitative leap in collection efficiency and recognition accuracy,
but also playing an irreplaceable role in multiple key fields. With
the continuous evolution and innovation of technology, fingerprint
recognition technology will continue to deepen its application in
security verification, identity management, and other aspects,
contributing to the construction of a more intelligent and secure
social environment.
Grow R307S Cheap 1000 Capacity USB Uart Optical Fingerprint Module
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