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Fingerprint Scanner TTL GT511C3 – 3.3V to 6V
₹2,825.00 Original price was: ₹2,825.00.₹2,600.00Current price is: ₹2,600.00. inc. GST
- Model: GT-511C3
- Operating Voltage(VDC): 3 to 6
- CPU: ARM Cortex M3 Core (Holtek HT 32F2755)
- Sensors: Optical
- Image Size: 202 x 258 Pixel
- Resolution: 450 DPi
- Effective Scanning Area(mm): 20 x 16
- False Acceptance Rate (FAR): 0.001%
- False Rejection Rate(FRR): < 0.1%
- Operating Temperature : -20°C ~ +60°C
- Default Baud Rate: 9600bps
- High-Speed, High-Accuracy Fingerprint Identification using the Smack Finger 3.0 Algorithm
- Read and Write Fingerprint Templates and Databases
- Simple UART protocol (Default 9600 baud)
- Capable of 1:1 Verification and 1:N Identification
- High-accuracy & high-speed fingerprint identification technology.
- Works well with dry, moist, or rough fingerprints.
- 200 fingerprints storage.
- Easy one-touch enrolment.
- Dimensions(mm): 37 x 17 x 9.5
- Weight: 6gm
The GT-511C3 Fingerprint scanner is defined as a small embedded module comprised of an optical sensor mounted on a small circuit board. The optical sensor scans the images of your fingerprint to recognize its pattern. Initially, we need to register each fingerprint that you want to store by sending the corresponding command and pressing your finger against the reader three times. The fingerprint data in the module is stored and configured in 1:1 or 1: N mode for identifying the person.
The inbuilt camera takes pictures of your fingerprint and then processes it using a powerful in-built 32-bit CPU ARM Cortex M3 IC. These images are further processed and converted into binary values by using the ARM Microcontroller coupled with EEPROM. Each fingerprint sensor captures an image of 202×258 pixels with a resolution of 450dpi and can enrol up to 200 fingerprints. Each fingerprint template will assign an ID from 0 to 199. During the detection process, it can automatically compare the scanned fingerprint with all 200 templates. If any match is found, it gives the corresponding ID number of that particular fingerprint using the Smack Finger 3.0 Algorithm on the ARM Microcontroller. The camera in the sensor surrounded by blue LEDs is used to take a clear image of the fingerprint. The module also has a green colour SMD LED to indicate power.
This module can directly interface with any 3.3V or 5V microcontrollers. But it requires a logic level converter to communicate with each other for working on different voltage levels. The module operates at 3.3V consuming about 130mA current. For enrolling a finger it nearly requires 3sec and 1 seconds to identify it. In case if the enrolled template count is less, the recognition speed will be high. This module offers wide applications such as access control, security, identification, and convenience.

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