A biometric factor is something physiologically unique about an individual, such as a fingerprint, facial image, iris, voice pattern, and handwriting. When an individual wants logical or physical access (depending on the implementation), a sample is taken of the authenticities’ biometric data, for example, a fingerprint. Then, the authenticator, using a previously enrolled version of the same biometric template can match the sample against the stored template to verify the individual’s identity. Biometrics is not secret, as everyone leaves fingerprints everywhere they go, faces and eyes can be photographed, voices can be recorded, and handwriting samples can be obtained. The security of the fingerprint authentication system, therefore, relies on the integrity and authenticity of the biometric information. Therefore careful evaluation must be done for the selection of the fingerprint authentication and Good practices should be followed during the implementation, enrollment, and administration of the fingerprint authentication system. In this paper, we intend to propose a high-speed method for fingerprint recognition based on minutiae matching, which, unlike conventional minutiae matching algorithms, also takes into account region and line structures that exist between minutiae pairs, allowing getting more structural information of the fingerprint and resulting in stronger and more accurate matching of minutiae. For Fingerprint thinning, the Block Filter is used, which scans the image at the boundary to preserve the quality of the image and extract the minutiae from the thinned image. The false matching ratio is better compared to the existing algorithm.