Fingerprint Enhancement Algorithm Research

In the recent years, automatic fingerprint identification technique (AFIT) , as a kind of biometrics technology, has been applied most widely. It mainly includes three phases: fingerprint image processing, feature extraction and matching. Until now ,it has drawn a substantial attention in the literature . In practice, due to variations in impression conditions, ridge configuration,skin conditions, the problems of acquisition devices, and noncooperative attitude of subjects etc., a 10 percentage of acquired fingerprint images is of poor quality. In order to ensure that the performance of the minutiae extraction algorithm will be robust with respect to the quality of input fingerprint images, an enhancement algorithm which can improve the clarity of the ridge structures is necessary.But there are a lot of questions and difficulties exists in the major algorithm to deal with the fingerprint singular point area and the specific operating unit. Therefore, in this paper, we deeply analyze and investigate the key algorithm of automatic fingerprint identification system—fingerprint-enhancement algorithm.The research contents are as follows:1, The fingerprint singular point area is a special region, in which the ridge direction changes rapidly and the ridge frequency is different from the other area. With the condition existing, in this paper, a novel method, which is called two-step enhancement method, is presented to enhance the singular point area in the fingerprint image. First of all, a filter, based Rayleigh function, is applied to the area for band filtering, and next, we use eight direction Gabor filters with interval 22.5 degree to enhance this area respectively. The optimum sixteen directional subdomains images, which come from the eight filtered images, can be obtained by using quality index. Finally, we get the fingerprint enhancement image of the singular point area through synthesizing these subdomains images. 2,Compared with dominating algorithms based on the block level or the global level ,the paper proposes a new enhancement algorithm ,which is based on the region level. Firstly, the direction coincidence indicator is used to divide the fingerprint image into several regions with the same direction, and next, the "missed" blocks located in region and the neighbor are incorporated in the regions above, through this step, the regions can become 8-connected. After we computer the region frequency by using the region-level frequency estimate method , the region images are filtered by the Gabor filters. In fact, the method is the tradeoff. It not only solves the "devious problem" in the block-level method to a great extent, but also tries to drop down the space-time complication in the global level method.There are five chapters in this paper. The 1^st chapter is introduction, which introduces the general institutions and difficulties of fingerprint identification and fingerprint enhancement and the 2^nd chapter presents a fingerprint singular point area enhancement algorithm .Chapter 3 introduces a fingerprint enhancement algorithm based on the region level.The final 5^th chapter is conclusion and discussion.