Handwritten Signature Verification Based on Surf Features Using HMM
نویسندگان
چکیده
Handwritten signature broadly used biometric which include elevated intrapersonal variance .Signature are generally used as the personal identification apparatus for human that the necessitate for verification system. Two types verification is performed generally online (dynamic) and offline signature verification (static). The static is offline technology that is used for documents authentication, the dynamic is online technology for signal processing and pattern recognition. The main motive of handwritten signature verification is to reduce fraud in financial transactions, security in crossing the international borders and boarding an aircraft. In this paper present the signature verification on Punjabi database of 50 persons. The features are extracted using the Gabor filter and matching is performed using SURF features and critical point matching. The classification is based on HMM classifier and the experimental results shows the verification accuracy rate of 97%. General terms: Biometrics, Signature verification, signature matching.
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