The Research Of Fast Fingerprint Matching Based On Local Structure Similarity Of Minutiae

Compared to other biometric identification technology, fingerprint recognition has the advantages of uniqueness and stability, Fingerprint recognition as the most widely used Biometric Authentication has a long history, Especially, with the rapid development of information processing technology, fingerprint identification obtains a wider market and are increasingly used in embedded devices. At the same time, Fingerprint recognition algorithm confronts the new challenges and demands. Reliable and fast fingerprint identification has more pressing needs. This paper is about the study and improvement of some key algorithms of automatic fingerprint recognition, including the fast enhancement and matching of fingerprint image, thus, improving the overall performance of fingerprint identification system.Fingerprint image enhancement is a very step of fingerprint preprocessing, the enhanced effect will have a direct impact on the follow-up process of the fingerprint identification. Based on the traditional two-dimensional Gabor filter enhancement, the paper improved the existing fingerprint image enhancement algorithm by dividing two-dimensional Gabor filter into the combination of one-dimensional Gauss filter. The implement of one-dimension decomposition of two-dimensional Gabor filter can greatly reduce the complexity and the number of operations. Experimental result shows that the improved fingerprint enhancement algorithm can reduce the running time greatly and also maintain the effect of fingerprint enhancement.Fingerprint image matching algorithm as the final step in fingerprint recognition is also the one of the most core research content. Because of the small storage template and high security, Fingerprint matching based on point pattern has been a hot research. However, many fingerprint matching methods have the disadvantages of large computational complexity, slow matching speed and low matching precision, Reliable and fast fingerprint matching in the automated fingerprint identification system remains a challenge. This paper presents an improved minutiae-based fingerprint fast matching algorithm which can speed up the matching speed and ensure the robustness to non-linear deformation by building the minutiae-centered annular region as the local structure of feature points. We can find the matching minutiaes more quickly through the annular region because it is a small region of fingerprint. In general, the local structure similarity of feature points has higher reliability. Therefore, compared with the global match, the improved method will have better robustness to the nonlinear deformation. In addition, the annular area is larger than the local neighbors area of the local matching, so the annular area contains more minutiaes than the local neighborhood of the local matching, thus, the matching results will be more reliable. Experimental result shows that the improved matching method has better performance in processing rate and accuracy.We apply these two improved methods in the fingerprint identification system, experimental result using the four databases of FVC2004 shows that the improved fingerprint rapid enhancement and fast matching methods can greatly improve the speed of fingerprint identification.