09-09-2017, 11:03 AM
Biometric systems operate on biometric behavioral and physiological data to identify a person. Biometric behavior parameters are signature, gait, speech and keystroke, these parameters change with age and the environment. However, physiological features like face, fingerprint, palm print and iris remain unchanged throughout a person's life. The biometric system operates based on one of the verification or identification modes. In the verification mode, the point is to combine the captured characteristics of a person with a template to give an answer, yes or no. The identification mode recognizes the person by matching their biometrics with each template in the database.
Because the simplicity and profitability of physiological biometrics are the first choice of any developer. in the other hand the fingerprint between physiological biometrics is the most popular and most used because of its feasibility, distinctive character, permanence, accuracy, reliability and acceptability. Fingerprint pairing systems can be classified into two categories, correlation based approaches and minutiae based approaches. In approximations based on correlation, the pixel similarity is estimated. The first step in this type is to find one or two singular points; by singular point we mean core of fingerprint and delta. They use unique points as an image reference point and rotation handle. If the fingerprint image contains only a single point, it must be rotated at various angles to determine the most appropriate grade. Sir Henry in 1900 classified the fingerprints into five classes, Arch, store arch, Whorl, Right loop and Left loop. In arc types there is no central point, this will be a problem when using correlation-based approaches. On the other hand, Minutia-based approaches are more popular. This approach uses some local features on the fingerprint ridges called minutiae points. Based on the forms of the crests and their collisions, the points of the minutiae are called endings of crests, forks, crossing points and spurs, etc., the most common features used are terminations and bifurcations.
Because the simplicity and profitability of physiological biometrics are the first choice of any developer. in the other hand the fingerprint between physiological biometrics is the most popular and most used because of its feasibility, distinctive character, permanence, accuracy, reliability and acceptability. Fingerprint pairing systems can be classified into two categories, correlation based approaches and minutiae based approaches. In approximations based on correlation, the pixel similarity is estimated. The first step in this type is to find one or two singular points; by singular point we mean core of fingerprint and delta. They use unique points as an image reference point and rotation handle. If the fingerprint image contains only a single point, it must be rotated at various angles to determine the most appropriate grade. Sir Henry in 1900 classified the fingerprints into five classes, Arch, store arch, Whorl, Right loop and Left loop. In arc types there is no central point, this will be a problem when using correlation-based approaches. On the other hand, Minutia-based approaches are more popular. This approach uses some local features on the fingerprint ridges called minutiae points. Based on the forms of the crests and their collisions, the points of the minutiae are called endings of crests, forks, crossing points and spurs, etc., the most common features used are terminations and bifurcations.