Study On Structure-based Fingerprint Representation And Matching Algorithm

Traditional security system,such as mechanical key,password/PIN and passport / ID card,may be forgotten,lost or stolen and cracked by an imposter. The emergence of biometrics has addressed these problems. Biometrics,automatic identification an individual by using certain physiological or behavioral characteristics associated with the person,has gained wide acceptance recently because of the unbridled violence of terrorism and hacker. Fingerprint (FP) recognition is a hot spot and the most widely used branch of biometric with many advantages,such as easier to use,higher reliability and lower cost. A number of commercial systems and research achievements exist for fingerprint recognition;however,the performance cannot satisfy the rigorous requirements of some special application. In this paper,the key technology -FP recognition algorithm is launched based on the analysis of current situation of automatic fingerprint identification system (APIS). The structure-based FP representation and its matching algorithm are proposed to address the shortcoming of traditional minutiae-based method,which makes use of limited information in FP images.In the former three chapters,we introduce the history,status quo and the development trend of APIS,the difficulties of FP recognition,and the object our research;also the combination and access method for the APIS;moreover,the anatomy of traditional method for FP recognition.In the forth chapter,the physics model of Gabor function for FP recognition is present. The optimal designed Gabor filters is illustrated theoretically and experimentally. The comparing experiments for two tessellated methods and two parameters selections are given for confirm the optimal filters.In the fifth chapter,the whole FP recognition algorithm is described in details,which made much improvement to enhance the performance.In the sixth chapter,the orientation specified filtered representation is described to reduce time consume of filtering operation,and then the ANFIS-based (Automatic Neuro-Fuzzy Identification system) matching algorithm is proposed. The experimentresults compared with other methods on the standard FP database (FVC2000 [22]-FP Verification Competition) are given.The compensated recognition algorithm is proposed to improve the recognition rate in the seventh chapter. This method could be used for reference by other FP technology,and also by other biometric,image and pattern recognition and classification,etc.The main conclusion,the shortage and the prospect of the research of this thesis are given finally.Structure-based FP recognition method not only makes best use of texture structure information contained in the gray level FP image but also reflect the local information. So it can offset the shortage of traditional method in limited area image. ANFIS-based matching algorithm and compensated recognition algorithm are robust to noise and distortion,and achieve a high accuracy. All of the experiments are tested on standard FP database,and compared accuracy with other related methods. The element and grate of what can result in error is analyzed and compared by experiments.