Finger vein recognition is a smart and consistent biometrics which makes use of the uniqueness of the vein patterns of human finger for personal identification in security systems. Interval type-2 fuzzy theory is applied in this paper for enhancing the finger vein biometric images in a unique way. Membership function aggregate for the required fuzzy set is calculated using Einstein T co-norm. Minutiae features are extracted using crossing number and Euclidean distance is used for feature matching. The proposed method shows superior enhancement and accurate matching results. © 2017 IEEE.