Dorsal hand veins features extraction and recognition by correlation coefficient

One of the most convenient biometrics approaches for identifying a person is dorsal hand veins recognition. In recent years, have acquired increasing attention because its characteristics such as universal, unique, permanent, contactless, and difficulty forging, also, remain unchanged when human being grows. The captured image suffers from many differences in lighting conditions, brightness, existing hair, amount noise. To solve these problems, this paper aims to extract recognize based on largest correlation coefficient. proposed system consists three stages: 1) preprocessing image, 2) feature extraction, 3) matching. order evaluate performance, two databases been employed. test results illustrate correct recognition rate (CRR), accuracy first database are 99.38% 99.46%, respectively, whereas CRR, second 99.11% 99.07% respectively. As result, we conclude that our method recognizing feasible effective.