Design of fingerprint recognition module based on FPGA

Project background and feasibility analysis

The name of this project is: FPGA-based fingerprint identification module design.

The main content is: This module uses xilinx Spartan 3E series XC3S500E FPGA as the core control chip, extracts the fingerprint image through Fujitsu's MFS300 sliding capacitive fingerprint sensor, and then performs grayscale filtering and image on the extracted fingerprint image. Enhancement, binarization, binary denoising, refinement and other pre-processing, to obtain a clear fingerprint image, and then extract fingerprint feature points from the clear fingerprint image, and store it in the external FLASH as a file template. When the fingerprints are compared, the same method is used to obtain a clear fingerprint image, and a comparison template is established. Then, the comparison template and the template are compared using a point pattern matching algorithm to obtain a comparison result. The module uses embedded soft core to realize system management, and realizes fingerprint recognition by hardware, which ensures the integrity of the system function and the correctness of recognition. The identification module can be used for many aspects such as access control, attendance, security check, safe cabinet, etc., and can also be used online with computers and other devices to meet different needs of various aspects, so its design has a wide application prospect and market value.

a discussion of the key technologies and innovations of the project;

2.1 Key technologies of the project

2.1.1 Collection of fingerprint images

This module uses the MFS300 sliding capacitive fingerprint sensor of Fujitsu Corporation of the United States to extract and save fingerprint images. This fingerprint sensor uses standard CMOS technology and includes an 8-bit A/D converter that operates over a wide voltage range of 2.8 V to 5 V. It automatically detects the presence of fingerprints on the sensor and enables online acquisition. It can greatly reduce the size of the sensor (13.3 & TImes; 3.6mm2) while ensuring high resolution (500dpi) of the fingerprint image. Then the XC3S500E uses its SPI port to read and write the internal registers of the MFS300 to control it to complete the task of fingerprint acquisition.

2.1.2 Preprocessing of fingerprint images

The main steps of image preprocessing include: pattern calculation, image enhancement, binarization, binary denoising, refinement, and so on. The purpose of preprocessing is to improve the quality of the input fingerprint image to improve the accuracy of feature extraction. The original fingerprint image generally has problems such as noise pollution, ridge breakage or ridge blur, and image enhancement (using filtering techniques) is needed to improve the quality. Since the fingerprint feature is only included in the shape structure of the ridge line, the ridge lines of different shades and widths are turned into fine ridge lines of the same gray scale and single pixel width by binarization and refinement, so as to facilitate feature extraction. .

2.1.3 Feature extraction and comparison of fingerprint images

The system extracts the global features and detailed features of the pre-processed fingerprint image through the detail feature extraction algorithm, and stores the fingerprint image feature parameters into the peripheral FLASH to establish a fingerprint database. In the recognition mode, the system extracts the fingerprint image feature parameters in the same way, stores them in the extended SRAM, and then compares the data in the peripheral FLASH and the extended SRAM with the dot pattern matching algorithm, and finally outputs the comparison result.

2.1.4 Problems that the system as a whole needs to consider

An effective fingerprinting system relies not only on identification algorithms, but also on many other aspects, including registration and identification processes, exclusion spoofing, and security considerations. We must respond to these issues in order to achieve effective identification.

2.2 System Innovation

Throughout the world, many fingerprint recognition events: fingerprints, fingerprints, fingerprints, social security, fingerprints, kindergarten attendance, fingerprints, kindergartens, fingerprints, bank withdrawals, fingerprints, supermarket shopping, fingerprints, laundry, fingerprints, New phenomena such as fingerprints on mobile phones, fingerprints on computers, and so on have emerged in an endless stream. Fingerprint recognition has been associated with people's lives. Fingerprint products show broad market development prospects and huge profit margins.

Since this development board has VGA, RS232, keyboard/mouse and other interfaces, it can be easily applied in many products, so that the product has the function of fingerprint recognition. For example, it can be used in conjunction with a fingerprint safe (cabinet), a fingerprint door lock, an IC card system, a car boot system, or a device such as RS232 and a computer. At the same time, most of the current fingerprint identification and authentication systems are implemented by DSP or ARM. Such an embedded system is difficult to achieve miniaturization and integration, and it is impossible to implement SOC, so that the application of fingerprint recognition in miniaturized portable products is limited, and this module With FPGA as the core control system, because FPGA has the advantages of high integration, low power consumption, short development cycle, etc., if the module is designed successfully, the miniaturization, integration and SOC of the fingerprint identification module can be realized, so that fingerprint recognition can be applied to More fields bring more convenience and security to people's lives, but also have broader market development prospects and greater profit margins.

Technical maturity and reliability discussion

This module uses xilinx Spartan 3E series XC3S500E FPGA as the core control chip. This chip adopts 90ns advanced technology and has a maximum capacity of 500,000 gates, which is enough to meet the design requirements. Fujitsu's MFS300 sliding capacitive fingerprint sensor uses standard CMOS technology and contains an 8-bit A/D converter. It can operate in a wide voltage range of 2.8 V to 5 V, and can automatically detect whether a fingerprint arrives at the sensor and realize Online collection. It can greatly reduce the size of the sensor (13.3 & TImes; 3.6mm2) while ensuring high resolution (500dpi) of the fingerprint image. The system uses the SPI port of the XC3S500E and the MPS300 for data transmission, which makes the transmission more convenient, the transmission speed is faster, and the anti-interference ability is stronger. In addition, the module uses the embedded soft core to realize the system management, and realizes the recognition algorithm by hardware to ensure the integrity of the system function and the correctness of the recognition. The recognition algorithm uses the feature point matching algorithm recommended by the US FBI to realize fingerprint recognition, and more guarantees the realization of system functions.

Project implementation plan

1. Basic functional block diagram and description of the program

Briefly describe the technical solutions for implementing this project by means of a block diagram and a brief description.

Figure 1 System block diagram system uses xilinx Spartan 3E series XC3S500E FPGA as the core control chip, through the MFS300 sliding capacitive fingerprint sensor for fingerprint image acquisition, automatic A / D conversion, and the converted digital signal through the SPI port Transfer to the FPGA core control unit for fingerprint registration or fingerprint comparison. The extended SRAM and Flash are used to store temporary data and fingerprint data information when the fingerprint program is running. The PROM configures the FPGA at power-up. The keyboard is used to implement module mode switching and module password setting. The RS23 interface can be operated online with devices such as computers to facilitate the expansion of system functions. The system uses the embedded soft core to realize the system management, and realizes the recognition algorithm by hardware to ensure the integrity of the system function and the correctness of the identification.

2. The required development platform

Basic functions, functions, and interfaces required to implement this Solution

The required target FPGA development platform, a brief description of why this platform is needed

Do you need other supporting development tools?

The required hardware development platform is: the primary board Spartan-3E

Partan 3E series XC3S500E FPGA is used as the core control system. The SPI port is used to access the registers of the MFS300 sensor to realize the data acquisition task. The DSP soft core is embedded in the internal to realize image preprocessing, feature parameter extraction and matching. The peripheral FLASH stores the fingerprint data information, establishes a fingerprint database, and establishes a human-computer interaction interface through the LCD display module.

The required software development platform is: Xilinx ISE 9.1i, Matlab, etc.;

The Xilinx ISE 9.1i is used to control the FPGA, and the Matlab is used to simulate the filter, the algorithm, and the soft core.

3. Modules to be developed during the implementation of the program

The main modules of the functions that need to be developed and developed in this solution, and the way of development

The modules that need to be specifically developed include the data acquisition module, the preprocessing module of the original image, the algorithm identification verification module (the Dsp algorithm is implemented by Matlab, embedded in the FPGA as a soft core), the keyboard operation module, the LCD display module, and the like.

4. The final performance indicators of the system

Discuss the objectives envisaged when the project is finalized.

It can accurately and effectively complete fingerprint feature extraction and fingerprint identification verification.

Other resources needed

1. Design input and output function daughter board

Daughter board function description, interface description, time, mode

Need a U.S. Fujitsu MFS300 sliding capacitive fingerprint sensor

16 buttons

LCD piece

2. Test equipment

List the test equipment (multimeter, oscilloscope, spectrum analyzer, logic analyzer, etc.) required during the implementation of the solution

The test equipment required is a multimeter, an oscilloscope, a logic analyzer, a power supply, and the like.

3. Policy, development tools

List the simulations, development tools, etc. that are needed during the implementation of the solution.

Simulation tools use Modelsim, development tools include Ise, Matlab, etc.

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