Capacitive Fingerprint Reader

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

1. Fingerprint reading application (case A) include devices: scammer and comparing
terminal

2. Fingerprint reading application (case B) includes devices: scanner terminal and
comparing server
1) Create database and list for fingerprint
2) Obtain fingerprints
3) Upload fingerprint
4) Comparison
5) Download results

3. Online comparison application (case A) includes devices: ID input terminal, fingerprint
database, comparator:
(1) terminal module
1) Create database and fill it by fingerprint’s data

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2) Input user ID, send ID to server with fingerprints
3) Download from server fingerprint according user ID to terminal, save or keep in buffer
4) Scanning and comparison of fingerprints

4. Online comparison application (case B) includes devices: download fingerprint to
terminal, compare in terminal.
(1) terminal module
1) Create database and fill it by fingerprint’s data
2) Download the fingerprint by stuff according user permission from server to module

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3) Scan user’s fingerprint and compare it with loaded fingerprint

5. Online comparison application (case C) includes devices: terminal scanning fingerprint,
uploading server for “1:1” comparison
(1) terminal module
1) Create database and file it by fingerprint’s data
2) Scan fingerprint, obtain fingerprint’s characteristics (at fingerprint module)
3) Upload fingerprint’s characteristics to server
4) Accept uploaded characteristics and compare with certain characteristics from database
5) Return comparison result

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6. Online comparison application (case D) includes devices: terminal scanning fingerprint,
uploading server for “1:N” comparison
(1) terminal module
1) Create database and fill it by fingerprint’s data
2) Scan fingerprint, obtain fingerprint’s characteristics (at fingerprint module)
3) Upload fingerprint’s characteristics to the server.
4)Accept uploaded characteristics and compare with all characteristics from databse
5) Return comparison’s result.

7. Fingerprint card application (case A): loader of fingerprint from database by card ID,
fingerprint scanning and comparing terminal
(1) terminal module
1) Create database and fill it by fingerprint’s data
2) Read card’s ID at terminal
3) Send ID to the server for getting fingerprint characteristics
4) Download the characteristics to fingerprint module.

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5) Compare scanned fingerprint with download one

8. Fingerprint card application (case B): fingerprint memory card saver, fingerprint memory
card downloader and comparator
(1) terminal module
1) Create database and fill it by fingerprint’s data
2) Save fingerprint characteristics of the user into the memory of card
3) Use the card to obtain fingerprint characteristics and save them in it.
4) Compare characteristics of scanned fingerprint and kept in card memory one

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5) Delete data from card’s memory after successful comparison.

Specifications

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