The handwritten signature has been the most natural and long lasting authentication scheme in which a person draw some pattern of lines or writes his name in a different style. The signature recognition and verification are a behavioural biometric and is very challenging due to the variation that can occur in person’s signature because of age, illness, and emotional state of the person. As far as the representation of the signature is concerned a classical technique of thinning or skeleton is mostly used. In this paper, we proposed a new methodology for signature verification that uses structural information and original strokes instead of skeleton or thinned version to analyse the signature and verify. The approach is based on sketching a fixed size grid over the signatures and getting 2-Dimensional unique templates which are then compared and matched to verify a query signature as genuine or forged. To compute the similarity score between two signature’s grids, we follow template matching rule and the Signature grid’s cell are mapped and matched with respect to position. The proposed framework is fast and highly accurate with reduce false acceptance rate and false