In this paper palmprint and knuckleprint ROI׳s are extracted and transformed using the proposed sign of local gradient (SLG) method to obtain robust vcode and hcode image representations. Corner features are extracted from vcode and hcode by performing eigen analysis of the Hessian matrix at every pixel. The matching is performed using the proposed HUF dissimilarity measure. Finally scores obtained for both traits (i.e. palm and knuckleprint) are fused to get multi-modal fusion score using the SUM rule. The overall architecture of the proposed multi-modal biometric system is shown in Fig. 2.