An approach for on-line signature authentication using Zernike moments

In this work, shape analysis of the acceleration plot, using lower order Zernike moments is performed for authentication of on-line signature. The on-line signature uses time functions of the signing process. The lower order Zernike moments represent the global shape of a pattern. The derived feature, acceleration vector is computed for the sample signature which comprises on-line pixels. The Zernike moment represent the shape of the acceleration plot. The summation value of a Zernike moment for a signature sample is obtained on normalized acceleration values. This type of substantiation decreases the influence of primary features with respect to translation, scaling and rotation at preprocessing stage. Zernike moments provide rotation invariance. In this investigation it was evident that the summation of magnitude of a Zernike moment for a genuine sample was less as compared to the summation of magnitude of a imposter sample. The number of derivatives of acceleration feature depends on the structural complexity of the signature sample. The computation of best order by polynomial fitting and reference template of a subject is discussed. The higher order derivatives of acceleration feature are considered. Signatures with higher order polynomial fitting and complex structure require higher order derivatives of acceleration. Each derivative better represents a portion of signature. The best result obtained is 4% of False Rejection Rate [FRR] and 2% of False Acceptance Rate [FAR].

Research highlights
► Lower order Zernike moments are selected using acceleration vector.
► Summation values of a Zernike moment for a genuine signature sample was less.
► Polynomial fitting order and derivative of acceleration vector are found.