Differential-code-based Fingerprint Minutiae Extracting And Spiral-vector-based Matching

As the rapid development of internet technology and the information technology, the traditional security systems such as keepsake, user name and password can be no longer meet people's needs. So the bio-identification technology was born, which is unique and remains a lifetime. These features of biological recognition technology make it an excellent key in identity authentication system. As the oldest and the relatively more mature biometric technology, fingerprint recognition technology has been widely used in the financial, judicial and other security systems. However, the current fingerprint identification system performance can not meet the increasing requirements, many aspects of technology could be improved.In this paper, several key technologies of fingerprint recognition are studied and several viable solutions are put forward. Specifically summarized as follows:1. In this paper, Fingerprint image pre-processing work is on the study, highlighting the orientation field and in accordance with the orientation field extraction technology to enhance fingerprint technology. Using the information of orientation field to detect core. Compare with the traditional way, this method is simpler and faster.2. The traditional way based on ridge thinning has the defect of time-consuming and many spurious minutiae. In view of this limitation, a new algorithm for extracting minutiae based on differential code is proposed. At the beginning, the differential code is got by tracing ridge boundary; subsequently, the turning point is detected through the differential code with the special characteristic for different features, where the minutiae existing. Three different methods are chosen to compare with the proposed approach. The results show that it can detect minutiae with less computational cost and lower false detection.3. The way we generally using to match fingerprint is point mode, which needs to find a reference point and match the details by translating and rotating points. The calculation is complex and it costs a lot of time. To address this issue, this article constructs a spiral vector and makes core as the reference point. We use orientation field and minutiae number both as the matching materials. We should only compare two spiral vectors to get the matching result. Analysis of the experimental data shows the validity of the algorithm.Finally, a summary is made and some future works are presented.