On the other hand, finger knuckleprint is relatively newer biometric trait and very limited amount of work is reported. In [45], Zhang et al. have extracted the region of interest using convex direction coding. Correlation between two knuckleprint images is used for identification which is calculated using band limited phase only correlation (BLPOC). In[24], knuckleprints are enhanced using CLAHE to address non-uniform reflection and SIFT key-points are used for matching. In [43], the knuckleprint based recognition system that extract features using local Gabor binary patterns (LGBP) has been proposed. In [46], the Gabor filter bank is applied to extract features for those pixels which have varying Gabor responses. The orientation and the magnitude information are fused to achieve better results. In [47], local as well as global features are fused to achieve optimal performance.