Traditional fingerprints matching approaches are based on the minutiae and the texture characteristics. It is difficult for today's techniques to deal with the images captured by the solid-state fingerprint sensor...Traditional fingerprints matching approaches are based on the minutiae and the texture characteristics. It is difficult for today's techniques to deal with the images captured by the solid-state fingerprint sensors because the sampling area of these sensors is very small and only portion of the fingerprint can be obtained. In this paper, a novel integrated template has been built using several images and combining the minutiae with the texture characteristics at the same time. By using a kind of Gabor filters (eight directions) on the region around the reliable minutiae, local texture of each minutia termed as minutiacode is extracted. Further, a real-time matching algorithm using the integrated template is presented. The output is determined by the weight factor of the compound matching. Finally, experimental results show that this system performs well in reducing false reject rate (FRR).展开更多
文摘Traditional fingerprints matching approaches are based on the minutiae and the texture characteristics. It is difficult for today's techniques to deal with the images captured by the solid-state fingerprint sensors because the sampling area of these sensors is very small and only portion of the fingerprint can be obtained. In this paper, a novel integrated template has been built using several images and combining the minutiae with the texture characteristics at the same time. By using a kind of Gabor filters (eight directions) on the region around the reliable minutiae, local texture of each minutia termed as minutiacode is extracted. Further, a real-time matching algorithm using the integrated template is presented. The output is determined by the weight factor of the compound matching. Finally, experimental results show that this system performs well in reducing false reject rate (FRR).
