Automatic Fingerprint Verification System, Preprocessing And Feature Extraction Algorithms

In recent years, as the development of social and economic, the more accuracy, safty, practicality of identification were required. Among all kinds of biometric identification technology, people pay a great deal of concern on fingerprint recognition technology for it's many advantages, such as more convenient using, higher accuracy and lower cost. And as the most widely used and effective means of identity authentication, it have been widely applied in e-commerce, criminal identification, information security, and other fields.Fingerprint is a rugged finger skin lines. Once the human embryo created, the fingerprint will unchanged in whole life. Automated Fingerprint Identification System is an integrated system which concentrate the photoelectric technology, image processing, computer and networking, database technology, pattern recognition technology. In the view of the operation of the AFIS, based on the conclusion of the existing research results, I research the key algorithm in the fingerprint image preprocessing and feature extraction algorithm of the fingerprint authentication system in this paper. The author actualize the mainstream algorithm which used in the popular AFIS and experiment repeated, achieve the algorithm used in this paper with MATLAB7.Compared with the traditional system design, the system made some improvements:1. In the fingerprint image preprocessing course inosculate the step of the orientation field and the effective regional division, and evaluation the image quality directly. Using this algorithm can greatly reduce the processing time and avoid to handle of the invalid low-quality fingerprint.2. After estimate the fingerprint orientation field, an adaptive image enhancement algorithm which use different filters according to whether there have a furcation in the neighborhood was used to enhance the image and achieve a better effect.3. A feature extraction algorithm based on the binary image was used in the fingerprint feature extraction stage. Using this algorithm can not only get rid of the time used in thinning processing and avoid to introduce the pseudo-feature ,but also can extract the rich real minutia to make a sound foundation for further feature matching.