Online signature verification based on signatures turning angle representation using longest common subsequence matching

Online signature verification has been intensively investigated in several directions, such as the selected feature(s), similarity estimation and classification method. Local feature approaches combined with elastic distance metrics have the most successful performance so far. The Turning Angle Sequence (TAS) feature has not been extensively explored for signature verification, while the fusion of TASs of different scales, the Turning Angle Scale Space (TASS) is a new approach in this field. In this paper, we study the signatures TAS and TASS representations and their application to online signature verification. In the matching stage, a variation of the longest common sub-sequence matching technique has been employed. Experimental results using varying TAS(S) representation parameters on two publicly available signature databases, the SVC2004 and SUSIG, show the improved performance of the selected feature along with the chosen elastic distance measure on the equal error rate results of the online signature verification task.