In this paper, the authors will evaluate the use of SURF features in handwritten signature verification. For each known writer they will take a sample of three genuine signatures and extract their SURF descriptors. In this paper, off-line signature recognition & verification using neural network is proposed, where the signature is captured and presented to the user in an image format. Signatures are verified based on parameters extracted from the signature using various image processing techniques. The off-line signature recognition and verification is implemented using Matlab.