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In this paper, we propose a novel approach for identity verification based on the directional analysis of velocity-based partitions of an on-line signature. First, inter-feature dependencies in a signature are exploited by decomposing the shape (horizontal trajectory, vertical trajectory) into two partitions based on the velocity profile of the base-signature for each signer, which offers the flexibility of analyzing both low and high-curvature portions of the trajectory independently. Further, these velocity-based shape partitions are analyzed directionally on the basis of relative angles. Support Vector Machine (SVM) is then used to find the decision boundary between the genuine and forgery class. Experimental results demonstrate the superiority of our approach in on-line signature verification in comparison with other techniques.