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 | MX1.0-6Pin |
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.