Research And Implementation Of Fingerprint Classification And Identification

With the advent of the Internet Era, Biometric identification has attracted lots of attention and made great progress since the 80s. Fingerprint, one of the focuses in the personal identification field, is the hotspot and difficulty to researchers at home and abroad for a long time. Currently, an increasing number of automatic figerprint identification systems (AFIS) have been developed and expanded in people’s daily life, providing identity authentication and security protection. Although the theoretical research has made significant achivements, AFIS based on a large-scale fingerprint database is still to be further improved on accuracy and efficiency. Combined with the current development of digital image processing and pattern recognition techniques, this thesis researched several key algorithms based on large-scale fingerprint database, mainly focused on the optimization of the fingerprint image preprocessing, fingerprint classification and fingerprint identification. The main contributions of the dissertation are as following:1. Due to different kinds of noises, the fingerprint image prerocessing is very important to improve the quality of the collected images. On the basis of the analysis of current fingerprint identification technology dissertations, this thesis realizes the key steps of the fingerprnt image preprocessing. In the regard, a series of algorithm modifications about histogram equalization, orientation field calculation and image enhancement is proposed. This algorithm significantly enhances the contrast of the ridge and the valley line, ensure the accuracy and reliability of the details of the feature extraction.2. Usually the classic fingerprint classification algorithm needs to extract core and delta points. But in practical application, it’s highly possible that delta points don’t appear in the collected image, so extracting more classification features to make up for the defect will be very necessary. A new approach which combines the median line fitting with the minimum bounding ellipse method is presented to extract finger placement direction. Affine transformation is used for rotational processing after calculating the compensation of angle. In the aspect of fingerprint feature extraction, two-steps positoning method to extracting core points has been studied, which is on the basis of the orientation field consisitency coefficient and modified Poincare index algorithm. Because of the pseudo points, this thesis has proposed a sound set of methods based on human experience to help enhance the classification accuracy. Finally, a three-level fingerprint classification system based on the numbers, orientation, whorl’s radius and the arch’s direction of the core point, is presented. It can be used to implement the classification on the large-scale database.3. In order to optimize the commonly fingerprint identification algorithms based on the minutiae matching, a two-level fingerprint matching algorithm is developed. First, a discrim inative sub-structure is defined for each minutia, which includes a external congruent triangle and a triangle made up of the neighbor minutiaes. Then a similarity score is employed to decide whether it is necessary to get to the global matching. If the similarity score doesn’t reach a certain threshold, the potential images and candidate reference pairs which have gotten higher scores will be used in the movement and rotation transform. Finally, we can get the global matching score. The experiemental result shows that, this method greatly improve the speed and recognition rate of fingerprint identification system.4. This thesis systemically investigates the theory and methods of AFIS. In order to verify the feasibility and practicability of the automatic fingerprint identification algorithms, it combines the object-oriented idea with database technology and developes a platform that has been constructed by using Visual Studio 2010 and MYSQL. The software has been integrated with a variety of key algorithms, and can be used to test and research on fingerprint recognition algorithm.A large number of experimental data results show that, the algorithm modifications about the fingerprint image preprocessing can improve the mage definition effectively, and the proposed multi-level fingerprint classification approach result in high accuracy, as well as the two-level matching algorithm is effectiveness and efficiency.