Capacitive Fingerprint Reader (WS-13694) STM32F105, commercial fingerprinting algorithm, semiconductor sensor

Overview

The Capacitive Fingerprint Reader is a standard fingerprinting module designed for secondary development, allows fast and stable fingerprint verification.

Based on a high-speed digital processor STM32F105R8, combined with high-security commercial fingerprinting algorithm, and advanced semiconductor sensor, the Capacitive Fingerprint Reader becomes a simple but smart integration module, provides functionalities like fingerprint enrolling, image processing, feature finding, template generating and storing, fingerprint matching and searching, etc.

Features

• Easy to use by some simple commands, you don't have to know any fingerprint technology, or the module inter structure/calculation
• Commercial fingerprinting algorithm, stable performance, fast verification
• Sensitive detection, just touch the collecting window lightly, without pressing
• Allows to freely input/output fingerprint images, fingerprint feature file and other fingerprinting actions
• Dual communication, UART or USB
• Processor will enter sleep and wake up when detecting, achieves low power consumption
• Comes with rich related resources (software on PC, development SDK, tools, and examples for Raspberry/Arduino/STM32)

Applications

• Fingerprint lock
• Fingerprint safe deposit box
• Access control system
• Clock in and out

Specifications

Parameter	Value
Processor (CPU)	STM32F105
Sensor	Semiconductor (capacitive)
Module dimension (mm)	45 x 30
Sensor dimension (mm)	33.4 x 20.4
Image	DPI 508
Image resolution	192 x 256
Sensing area (mm)	9.6 x 12.8
Fingerprint capacity	1000 (expandable)
Security level	0-9 low to high security, 5 by default
Matching time	1s
False acceptance rate	0.0001%
False rejection rate	0.01%
Dynamic current	<40mA
Operating voltage	3.3V-5V
Communication	UART or USB
Anti-electrostatic	aerial discharge: ± 15KV
	contact discharge: ± 8KV

Dimension

Development Resources

Wiki : www.waveshare.com/wiki/Capacitive_Fingerprint_Reader

Selection Guide