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This paper proposes a fuzzy approach for Automatic off-line signature verification. Automatic off-line SV (Signature Verification) is an active area of research with numerous applications such as bank check verification, identity recognition, authorization in legal documents, etc. Over the decades two different types of computer based verification techniques arose: On-line and Off-line SV. Due to shape and size variability in signatures of the same writer and difficulty of verification problem, we present a fuzzy approach for SV. We use fuzzy approach for measuring the similarity degree between the reference and test signature using Takagi-Sugeno Fuzzy Inference System (FIS). Four types of local features (distance, angle, proportion, and distance to Centre of Gravity) are extracted from control points on set of training signatures and then these features fuzzified for training of FIS. According to the output of FIS, we make decision that test signature is forgery or genuine. Our algorithm is compared with some related works and the results of comparison are stated in section 7.