Guangdong Jishengke Industrial Co., Ltd. , https://www.suronart.com
The system is based on the ARM9 chip SamsungS3C2440AL, using Veridicom's fingerprint acquisition chip FPS200 as a hardware platform and embedded Linux as a software platform. In this research field, the recognition system based on PC platform has always been the focus of research. The ARM-based system implemented in this paper has the advantages of being light, easy to install, and low cost, and has a good development prospect.
1 system hardware design S3C2440AL main frequency is 400MHz, the highest is 533MHz; FPS200 fingerprint sensor consists of 256 × 300 capacitive sensor array, its resolution up to 500dpi, operating voltage range of 3.3 ~ 5V, the sensor has 8 ADC , And with 2 sets of sample and hold circuits.
2 Operating System Because embedded Linux has the advantages of small kernel, high efficiency, open source, and platform tools, the system uses embedded Linux as the operating system platform. The main steps to build the platform are:
(1) Download U-boot via JTAG;
(2) Configure the Linux Kernel and download it through the serial port;
(3) Development of FPS200 driver and dynamic loading.
3 Fingerprint Recognition Algorithm Flow Fingerprint recognition system can be divided into fingerprint image acquisition algorithm, image preprocessing algorithm, feature extraction algorithm and feature matching algorithm according to the main functions in the recognition process.
4 Principle of Fingerprint Segmentation Algorithm Set up a fingerprint image with N pixels. There are L gray levels (0, 1, 2, ..., L-1), and the number of pixels with gray level i is ni. Then, The image histogram is normalized and there is a probability density distribution:
Assume that the threshold t divides the image into two types of C0 and C1 (ie, object and background). C0 and C1 correspond to gray levels {0, 1, 2, ..., t) and {t+1, t+2, ..., respectively. L-1} pixels. The occurrence probabilities of C0 and C1 are:
5 Conclusion In this paper, an ARM9 processor is used as a platform to systematically implement an embedded access control system with good recognition results. The whole algorithm flow of the system design is given, and the image segmentation algorithm is emphasized. Compared with the previous research results, the system has the advantages of simple platform, high recognition rate, and rapid recognition. However, the effect of the system on distortion images is not very satisfactory and needs to be further strengthened in future studies.
Fingerprint access control system is a high-tech security facility based on biometric identification technology. It has been widely used at home and abroad in recent years and has become one of the signs of modern building intelligence. For some core confidential departments, such as important organs, scientific research laboratories, archives, and civil aviation airports, fingerprint access control systems can provide efficient, intelligent, and convenient authorization control. Because fingerprints have the characteristics of convenient portability, different people, and the same lifetime, fingerprint recognition is used as a means of identity authentication. Compared with traditional keys and passwords, security and credibility are greatly improved.