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3D Signature Biometrics Using Curvature Moments

A new biometric identification method is introduced in which a user “writes” his or her signature in the air. Accelerometers worn on a wrist device transmit acceleration data wirelessly to a host computer that processes the data and authenticates the user. This paper describes the use of curvature moments associated with 3D curves in both configuration space and velocity space as the features used for recognition. The mean vector and covariance matrix associated with a particular person are stored as template data in the device and wirelessly transmitted to the host computer when recognition is desired. The host computes the Mahalanobis distance from a new transmitted feature vector to the template data and authenticates the user if this distance is below twice the average Mahalanobis distance of each training sample. Experimental results show the difficulty of an imposter being recognized as the real person.