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 R503S fingerprint module with RGB ring indicator light, LED can be controlled by command. | R503 | R503-5V | R503-M22 | R503Pro | R503S |
Power Supply | DC 3.3V | DC 5V | DC 3.3V | UART: DC 3.3V USB:DC 5V | DC 3.3V |
Sensing Array | 192*192 Pixel | 192*192 Pixel | 192*192 Pixel | 192*192 Pixel | 160*160 Pixel |
Fingerprint Capacity | 200 | 200 | 200 | 1500 | 150 |
Size | M25 | M25 | M22 | M25 | M25 |
Connector | SH 1.0mm 6pin | MX 1.25mm 6pin | SH 1.0mm 6pin | SH 1.0mm 6pin | SH 1.0mm 6pin |
R503S Specifications
Model | R503S |
Type | Capacitive Fingerprint Module |
Interface | UART(TTL) |
Resolution | 508 DPI |
Voltage | DC 3.3V |
Fingerprint Capacity | 150 |
Sensing array | 160*160 pixel |
Working current | 20mA |
Standby current | Typical touch standby voltage: 3.3V, Average current: 2uA |
Fingerprint module external size | Diameter 28 (mm) |
Fingerprint module inner size | Diameter 25 (mm) (M25) |
Fingerprint module height | 19 (mm) |
Collection area | Diameter 15.5 (mm) |
Connector | SH1.0-6Pin |
LED Control | YES |
LED Color | RGB |
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 R503S user manual from this website link:
https://hzgrow.en.made-in-china.com
R503 Test program operation display video on Youtube: https://youtu.be/eD2xtwCWOmQ
If need SDK files,pls contact us. How to choose the fingerprint module?
The rapid progress of science and technology has given rise to many remarkable leaps in technology, among which, biometrics technology is particularly noteworthy, and fingerprint identification technology, as a key branch of the biometric field, has attracted much attention. Today, we focus on the fingerprint module, a tool for fingerprint identification, to provide a concise introduction.
Fingerprint recognition, as a kind of biometric technology, has long stood out among many identification technologies and has been widely used. The root cause of the public trust is that each person's fingerprint is unique and has a lifelong invariance, just like a personal biological ID card, which provides extremely reliable credentials for identity verification. Fingerprint module captures and analyses the fingerprint image to verify the identity of an individual, and its core process covers image acquisition, feature extraction and pattern comparison.
Nowadays, fingerprint modules mostly use optical and semiconductor sensors to achieve fingerprint capture. Optical sensors, as an earlier technology, rely on the principle of light reflection; while semiconductor sensors make use of the conductive properties of the human body. Both have their own merits, optical sensors are better in terms of environmental adaptability, while semiconductor sensors are more advantageous in terms of size and power consumption, so users can choose flexibly according to their actual needs.
With the rapid development of artificial intelligence, the accuracy and speed of fingerprint modules continue to improve. Deep learning algorithms can mine complex features from massive fingerprint data, significantly improving recognition accuracy. In addition, the integration of live body detection technology effectively prevents attacks on forged fingerprints and ensures system security.
Internationally, a series of standards have been set for biometrics, specifying the performance requirements of fingerprint modules, such as false rejection rate and false acceptance rate, guaranteeing the interoperability and reliability of different products, which has also become an important basis for the selection of fingerprint module suppliers.
Although the current fingerprint module is quite mature, the technological progress never stops. As the application of fingerprint modules becomes more and more widespread, the security requirements of users will only get higher and higher, which poses a challenge to fingerprint modules. Practitioners need to constantly refine their fingerprint modules to meet higher security standards.
Looking ahead, fingerprint modules will be used in a wider range of applications, which means that fingerprint identification technology must have a higher degree of adaptability and compatibility to meet the needs of diverse applications. At the same time, technological innovation will never stop, and future fingerprint modules are expected to achieve more breakthroughs in miniaturisation, low power consumption and high performance.
Therefore, when choosing a fingerprint module, it is necessary to consider the technology, security, privacy protection, and future development trends and other dimensions, in order to select a fingerprint module that meets their needs.