Automated Fingerprint Identification System

Biometrics technique is the automatic identification of a person based onhis/her physiological or behavioral characteristics. Due to the uniqueness andinvariability of fingerprints, the fingerprints identification is becoming a mostsecure, reliable, convenient alternative to the traditional identification methods,and it is an ideal and feasible biometrics technique comparatively. This paperdescribes the structure and working principle of the biometrics technique andAutomatic Fingerprint Identification System (AFIS), analyses the developmenthistory and the application, investigates status of fingerprint imagepreprocessing, minutiae extraction, fingerprint classification and matching, andprovides an in-depth study and analysis on the current popular of fingerprintsimage preprocessing, and fingerprint feature extraction algorithm. The mainresults for the research are as follows:1. A fingerprint segement method based on gray level statistics is proposed,which can eliminate the isolated pieces arised from the segmentation process,with robustness to noise and practicability.2. An improved Gabor-based fingerprint image enhancement method isproposed from the research of image enhancement algorithm and effect forfixed direction filter. According to the fingerprint ridge characteristics, the ridgefrequency is accurately calculated via ridge projection signal spectrum analysis.Experiments show that the method has good effect in ridge eonglutination area.3. Taking fingerprint image as a signal which is locally stationary butnon-stationary as a whole, the paper puts forward a probabilistic approximationmethod for the ridge orientation and frequency. Experimental results indicatethat the method has prominent effect on fingerprint images, and improves theaccuracy of minutiae extraction.4. According to the fingerprint image noise characteristics, a directionmedian filtering algorithm is designed, which can filter the impulse noise in thefingerprint image. The algorithm uses local threshold to binarize the fingerprintimages, contributes to the protection of the ridge local information, and avoidsintroducing too many errors in the binarization process. Experimental resultsprove that the algorithm is quite effective. 5. A minutiae extraction method based on the information fusion isproposed in order to solve the problem that the pseudo minutiae arised from theimage preprocess is diffcult to eliminate. The method filtrates the minutiae byfusing two results of different preprocess methods, and then eliminate pseudominutiae according to its structure. Experimental results show that the methodcan not only effectively eliminate the pseudo minutiae arised from the imagepreprocess, but also eliminate the pseudo minutiae caused by image acquisitionor quality et al.