The proposed sign of local gradient (SLG) method transforms ROI׳s of palmprint and knuckleprint samples into vcode and hcode that are more stable than gray-scale image and can provide robust features as shown in Fig. 6. The gradient of any edge pixel is positive if it lies on an edge that is created due to a transition from light to dark shade (i.e. high to low gray value) as shown with green in Fig. 5(b) and (c); otherwise it will be negative or zero. Hence all edge pixels can be divided into three classes of +ve, −ve or zero gradient values. The sobel x-direction kernel of size 3×3 and 9×9 is applied in Fig. 5(a) to obtain Fig. 5(b) and (c), respectively. Bigger size kernel produces coarse level features while smaller produces fine level but noisy features as shown in Fig. 5(c) and (b).