ARM9-Based Fingerprint Collection And Identification System Development

Nowadays, the fingerprint is most widely used. Fingerprint biometric identification plays an important role in identity, at present, most of fingerprint identification platforms connect PC desktop application system, which lead the application of fingerprint identification system to the higher cost and not universal. Therefore, for the broad market prospect and the research value, it is necessary to develop embedded platform of high recognition rate, processing speed, good scalability and cheap.Firstly, designing a practical BIOS on the basis of embedded hardware structure forming with Samsung ARM9 processor core S3C2440A and the peripheral circuit designing. In this platform, the new type of fingerprint sensor in FPC1011F ARM9 system hardware and software designing both collecting in MATLAB fingerprint data, proving acquisition excellent performance.On the basis of acquisition to fingerprint as follows:1. Using the VC 6.0 platform to research gray image segmentation algorithm, Gabor filtering, fixed threshold value method, mathematical morphology, refinement algorithm, and then research in advanced algorithms, filter enhancement, partition binary, refined and fingerprint pretreatment.2. Researching the fingerprint extraction algorithm on the basis of the fingerprint pretreatment, using eight neighborhood figure law to extract a fingerprint endpoint and fork points, and propose using direction field and Poincare formula of the method of combining, the extraction of the fingerprint singularity, and verifying on the base of VC 6.0 platform.3. After extracting the feature points of fingerprints, then using singular point calibration which extracted from singularity and Poincare form direction field, overcoming the shortcomings of great memory space because of using ridge line calibration method, processing time and poor quality fingerprint low recognition rate.4. The algorithm of reference Rossi equality, which proposed based on polar conversion, adopting size variable confines the box to adapt the fingerprint nonlinear deformation, center matching algorithm, then verifying the algorithm the VC 6.0 platform in the test standard results with the FPC1011F fingerprint match fingerprint sensor acquisition fingerprint image database.Through a series of practical acquisition recognition experiment proof, it is effective of the identification system, which proves poor quality fingerprints can be better recognized on the matching algorithm in this paper, and also can be more robust to deal with the nonlinear deformation fingerprint image, reducing the rate of fake fingerprint matching and shorten matching time. The research laid the foundation for embedded fingerprint identification algorithm transplant validated by experiment and the wide application of the embedded identification system.