Design and implementation of fingerprint collection device based on ARM

1 Introduction

In the field of personal identification, fingerprint recognition, as one of the most mature biometric technologies, has become the first choice for many applications. Compared with PC environments, embedded systems are small in size and low in power consumption. Due to their relatively specific functions, they have certain advantages in stability, reliability and security. Therefore, embedded systems are now not only used in mobile devices, but also increasingly used in identity recognition systems in fixed locations.

WinCE.Net embedded operating system is a newly developed operating system launched by Microsoft. It has preemptive multitasking function and powerful communication ability. It is specially used in non-PC fields such as information equipment, mobile applications, consumer electronics and embedded applications. It has been developed to version 5.0. The fingerprint acquisition equipment involved in this article works on an embedded system with ARM920T as the core. The purpose of designing this system is to conduct application research on portable fingerprint recognition instruments and provide a fingerprint recognition algorithm platform.

2 Design and Implementation of Fingerprint Collection System

The system uses the embedded 32-bit ARM device S3C2440 as the main control CPU, and consists of seven parts: fingerprint image acquisition module, core processing module, RAM, EEP-ROM, external memory, LCD display module, and interface module. Figure 1 shows the system structure block diagram.

2.1 Fingerprint collection module

The existing optical sensors are large in size, and the imaging results must be transformed before they can be used. This acquisition system is designed using Veridicom's FPS200 solid fingerprint recognition sensor. FPs200 is a fingerprint recognition sensor with superior performance, low power consumption and low price. Due to its special EDS protection, extremely narrow physical size, and unique power saving characteristics, the sensor is particularly suitable for use in embedded systems. The main principle is that a two-dimensional metal electrode array is integrated in the fingerprint image sensing area, each electrode acts as one pole of the capacitor, and there is a passivation layer between the two poles on the sensor surface as the dielectric layer of the capacitor. Because the ridges and valleys of the fingerprint will produce different capacitance values ​​when in contact with the sensor, measuring these different values ​​will form an image.

Compared with similar products, the performance characteristics of FPS200 are as follows:

(1) Support multiple interface modes. FPS200 has three interface modes, an 8-bit system bus interface, an integrated full-speed USB interface and an integrated serial peripheral interface, making the chip application design more flexible. The chip integrates a USB controller, which greatly reduces the workload of USB circuit design. At the same time, the USB interface protocol supports a higher transmission rate;

(2) Automatic fingerprint detection function. FPS200 can automatically detect whether a finger is placed on the sensor. If so, it will enter the working state; otherwise, it will enter the sleeping state. This design does not require polling to detect fingerprints, which improves the chip's operating efficiency;

(3) The FPS200 includes a new second-order A/D converter with low power consumption (75%); the FPS200 sensor unit spacing is reduced, which improves the mechanical strength of the sensor array.

The system uses the USB interface mode. Please note the following in the design: ① The working voltage of FPS200 is 3.3~3.6 V, while the power supply voltage of USB is 5 V, so a voltage conversion chip is used to implement voltage conversion; ② FPS200 uses MODEl and MODEO pins to select the interface mode. In the USB interface mode, the microprocessor interface mode and SPI are shielded. At this time, MODE[1:0]=l0b, and the internal ROM of FPS200 is used; the other pins CS0, CS1, MOSI, MOSO are shielded and the pins are left floating; a 12MHz crystal circuit is connected between XTAL1 and XTAL2; the multi-frequency oscillator inside FPS200 does not work. Figure 2 shows the connection circuit of the FPS200 sensor and the system.

2.2 Data processing and display

The system microprocessor module adopts ARM2440 development system, which adopts Samsung's ARM processor S3C2440 and is designed by 6-layer board. The development system integrates 64MBSDRAM, 64MB NAND Flash, 1MB B00T Flash, RJ-45 network card, audio input and output, USB Host, USB Slave, standard serial port, SD card socket and other device interfaces on the smallest possible panel (120mmx90mm), supports LCD/STN liquid screen interface, can connect various monochrome, pseudo-color, true color LCD screens, and contains touch screen interface. Data can be imported into U disk or PC hard disk in real time through the reserved USB port.

Today's SD cards are low-cost and large-capacity, so the storage module uses SD cards for image storage.

The LCD display module uses Samsung's 3.5-inch TFT (with touch screen). Through the touch function of the LCD screen or a USB mouse, the test system can be easily operated in a windowed manner.

3 System Software Design and Implementation

The host computer software is developed using the EVC tool and can be directly run in the Windows CE[5] environment. The host computer software is an important part of the control system operation. It mainly completes the human-machine interface, fingerprint image acquisition and processes the communication between the system and the acquisition module. The system software can be divided into the main program module, the communication module and the fingerprint acquisition module. The main program module mainly completes the interface display, human-machine interface, module call and other functions; the fingerprint acquisition module completes the fingerprint image acquisition; the communication module is responsible for receiving data and sending the modification instructions of the register controlled by the human-machine interface.

In order to collect fingerprints, the relevant registers of FPS200 must be initialized first. According to the technical requirements of the sensor, the values ​​of registers CTRLB, DTR, DCR and PGC are initialized to set the working mode of the sensor and adjust the sensor sensitivity to prepare for fingerprint collection. Changing the value of DTR can change the discharge time of the capacitor, DCR controls the size of the discharge current, and PGC controls the amplifier gain. When the DTR and DCR values ​​increase, the image becomes whiter and the contrast decreases.

By writing register CTRLA, you can select the fingerprint collection method. There are three fingerprint collection methods: collecting a row (GETROW); collecting a sub-image (GETSUB); collecting the entire image (GETIMG). Selecting different collection methods requires different row and column registers to be initialized. Figure 3 shows the system software flow chart.

4. Analysis of test results

Figure 4 shows the test results of the acquisition part. After comparing the images, it is found that the discharge parameters DCR, DTR and PGC of FPS200 have a certain influence on the clarity of the fingerprint. Among them, the DTR parameter controls the discharge time of the capacitor. Prolonging the discharge time can reduce the background noise of the fingerprint image; increasing the DCR parameter value can also reduce the fingerprint background noise, but increasing DCR and reducing DTR can maintain the clarity of the image; the PGC parameter controls the contrast between the fingerprint image and the background, and the parameters need to be adjusted according to different working conditions. The image of Figure 4 (a) was acquired under DCR = 0x01, DTR = 0x40, PGC = 0x0B (g = 3); the image of Figure 4 (b) was acquired under DCR = Ox01, DTR = 0x23, PGC = Ox00 (g = 1). When the finger is in good condition, the parameters of Figure 4 (a) are better than those of Figure 4 (b).

5 Conclusion

This paper designs a fingerprint acquisition system based on ARM, using FPS200 solid fingerprint sensor as fingerprint acquisition component. It reduces many software optimization image processes. Samsung's S3C2440 is used as the hardware platform and WindowsCE system is used as the software platform. It is very easy to implement external expansion, laying a good foundation for the next step of fingerprint recognition. The system is simple to operate and easy to carry. It is especially suitable for occasions where fingerprint acquisition instruments based on PC architecture are not suitable. It is low-cost and easy to promote.