Abstract
Biometrics is a kind of technology by which personal identification can be distinct, utilizes the physiological or behavioral characteristics. Fingerprint identification is the most well-developed of biometrics in the twentieth century and it is also steady and accurate. In fingerprint identification systems, the matching method using ridge ending points and bifurcation points as matching features is the most conventional. Furthermore, " Biometric Data Interchange Formats - Finger Minutiae Data " (ISO19794-2) has already been proclaimed by International Standard Organization (ISO) in 2005. As a result, minutiae-based fingerprint identification system will become an applied standard and mainstream in the future.The minutiae-based fingerprint identification system can beseparated into four procedures as follows, fingerprint imageacquisition, image preprocessing, minutiae extraction, and minutiae matching. In minutiae extraction procedure, false minutiae or the lack of correct minutiae usually happen because of poor image quality or the distortion in image processing process, especially the spurious minutiae make the greatest influence. Spurious minutiae not only decrease the acception ratio of genuine matching between corresponding fingerprints but also increase acception ratio of imposter matching between different fingerprints. In real systems, matching operation time will increase because of spurious minutiae.In this research, biconnected property of graph theory is applied on skeleton image, the meshed or complex loop regions resulted from poor image quality and reject the false minutiae in this area can be found. Hence, the spurious minutiae can be eliminated to increase matching performance. First of all, the bifurcation points extractedfrom skeletonized image are regarded as nodes in the graph, and the connected ridges are considered as edges of the graph. So far, an initialized graph of the fingerprint is obtained. Then we separate each independent biconnected subgraphs in the unreasonable regions in the skelentonized image and delete the nodes in subgraphs which are also false minutiae. It can be proved by the experimentalresults that the false matching ratio indeed decreased by applying the proposed minutiae purifying method and decreased the amount of minutiae. Therefore, the effects of this research can be validated.