Description
1. Integrated image collecting and algorithm chip together,
ALL-in-One
2. The flexibility to adapt to the conditions was the fingers,
whether it is dry fingers, wet fingers, light texture fingerprints
fingers, and old fingers, all have high recognition rate
3. The main application areas: can be embedded into a variety of
end products, such as: access control, attendance, safety deposit
box
The R502-AW has circular ring indicator light that can be
controlled by command, R502-A is built-into R502-AW.
R502-AW Specifications
Model | R502-AW |
Type | Capacitive Fingerprint Module |
Interface | UART(TTL) |
Resolution | 508 DPI |
Voltage | DC 3.3V |
Fingerprint Capacity | 200 |
Sensing array | 192*192 pixel |
Working current | 20mA |
Standby current | Typical touch standby voltage: 3.3V, Average current: 2uA |
Fingerprint module external size | 50*50*8.4 (mm) |
Effective collection area | Diameter 15.5 (mm) |
Enclosure material | Zinc alloy |
| Connect control board | K200-3.3/K202/K215-V1.2/K216 |
Connector | SH1.0-6Pin |
LED Control | YES |
LED Color | Purple and Blue and Red |
Scanning Speed | < 0.2 second |
Verification Speed | < 0.3 second |
Matching Method | 1:1; 1:N |
FRR | ≤1% |
FAR | ≤0.001% |
Work environment | -20C ---60C |
Work Humidity | 10-85% |
Anti-static capacity | 15KV |
Abrasive resistance intensity | 1 million times |
Communications baud rate (UART): | (9600 × N) bps where N = 1 ~ 12(default N = 6, ie 57600bps) |
Files
·Provide Free Reference SDK Files for Arduino, Android,.Net,Windows
and so on.
·Provide User Manual
You can download the R502-AW user manual from this website link:
https://hzgrow.en.made-in-china.com
R502-AW Operation display video on Youtube: https://youtu.be/Q82Zg4iFHOA
If need SDK files,pls contact us.
The quality of fingerprint images is the key to successful matching
The quality of fingerprint images plays a crucial role in biometric
technology, especially in fingerprint recognition technology. As a
key technology in fields such as identity verification and criminal
investigation, the accuracy and reliability of fingerprint
recognition are directly related to the overall performance and
security of the system. The foundation of all of this lies not only
in advanced algorithms, but also in high-quality fingerprint images
and matching fingerprint modules.
The fingerprint module is the core component of the fingerprint
recognition system, responsible for collecting and processing
fingerprint images. An excellent fingerprint module should have
high resolution, high sensitivity, and good adaptability, and be
able to capture clear and complete fingerprint images in various
environments. High quality fingerprint images can clearly display
the detailed features of fingerprints, such as ridges, valleys, and
endpoints, which are the key basis for comparing fingerprint
recognition algorithms.
If the fingerprint module performs poorly, the quality of the
captured images will be affected, such as blurring, breakage, or
the presence of a large amount of noise. These issues can mask or
distort key features of fingerprints, making it difficult for
recognition systems to accurately extract and compare, thereby
increasing the risk of misidentification and rejection rates.
Therefore, the performance of the fingerprint module directly
determines the quality of the fingerprint image, which in turn
affects the accuracy and reliability of the entire fingerprint
recognition system.
In addition to affecting accuracy, the performance of the
fingerprint module is also directly related to the system's
response speed and user experience. High quality fingerprint images
can reduce algorithm processing time and complexity, and improve
recognition speed. However, low-quality images require more
computing resources and time to attempt to extract sufficient
information for comparison, which not only slows down the system
response speed but may also lead to system crashes due to resource
depletion. In addition, the speed, painlessness, and accuracy of
the fingerprint module's collection process directly affect users'
acceptance and trust in fingerprint recognition technology.
To ensure the quality of fingerprint images and improve the
performance of fingerprint recognition technology, we need to start
from multiple aspects. Firstly, a fingerprint module with excellent
performance should be selected to ensure its high resolution, high
sensitivity, and good adaptability. Secondly, when collecting
fingerprints, attention should be paid to keeping the fingers dry
and clean, and avoiding the use of overly greasy or dry hand cream
to avoid affecting the clarity of the fingerprint image. In
addition, image processing algorithms can be optimized to further
remove noise, enhance contrast, and repair broken ridges to improve
image quality.
In summary, the quality of fingerprint images is the cornerstone of
the success of fingerprint recognition technology, and the
fingerprint module is a key component to ensure image quality. By
selecting high-performance fingerprint modules, optimizing the
collection process, and improving image processing algorithms, we
can continuously improve the accuracy and efficiency of fingerprint
recognition, providing more reliable technical support for fields
such as identity verification and criminal investigation.
