Abstract
The fingerprint recognition is the most widely used biometric recognition technology nowadays. International Organization for Standardization (ISO) had established and announced the standard format for the fingerprint template (ISO19794-2) since 2005.The minutiae is defined as ridge ending and ridge bifurcation, and minutiae information contains coordinate, direction and type. The matching speed under large scale fingerprint database is a challenge of fingerprint identification application. The minutia-based fingerprint matching method takes more matching time in general. Therefore, we use the triangular match quickly filter out the possibly correct fingerprint, and then use minutiae to find the correct fingerprint in the match. The quality of minutiae impacts fingerprint match indirectly. The fingerprint images are easily effected by air humidity and finger press. Even the same fingers, the fingerprint image can’t be obtained exactly the same each time, so the number of the minutiae, coordinates and the direction of the minutiae are different. The too closed unstable minutiae are produced by bad quality fingerprint images. The triangle is generated by minutiae, so unstable minutiae will generate narrow triangle. These narrow triangles can’t be match with other triangles in the fingerprint match. In my thesis, we would like to improve the recognition rate of triangle match by increasing stable triangles. The system after the triangular match process, the correction rate of selected fingerprints will increase. Because the triangle matching time is much shorter than minutiae matching time, thus we can decrease system total time under same system recognition rate by reduce the number of minutiae matching. On the other hand, the embedded system is getting more and more popular. We believe the fingerprint recognition system will not only develop in traditional PC. Hence we porting the designed fingerprint recognition system to the ARM platform, so that the usage of fingerprint recognition will increase. There are several kinds of embedded processor, such as arm, PowerPC, MIPs, SC-400 and so on. The main reason to choose the ARM platform to develop fingerprint recognition system as follows: The market share is the highest, it is the most effective and consume least electricity. We could develop practical fingerprint module from these advantages. If the system runs on ARM platform, the time of triangle match will be much lesser than minutiae match. Hence the recognition speed will also be fasten. This research adopts four sets of the FVC2002 fingerprint database. According to the experiment result, while the system recognition rate remain the same, we could select 1% of fingerprints out of the database after triangle match. It decreases to 0.75% and the number of times for minutiae match also decreases, while the matching speed became faster. The system speed increase between 11.19% and 21.58% in PC platform, between 22.3% and 27.35% in ARM platform.