Using empirical mode decomposition and Kullback-Leibler distance for online handwritten signature verification
by Toufik Hafs; Layachi Bennacer; Hanene Brahmia; Mohamed Boughazi; Amine Nait-Ali
International Journal of Applied Pattern Recognition (IJAPR), Vol. 6, No. 1, 2019

Abstract: The signature is one of the most accepted biometric modalities in the world. In this paper, we present a new method for online handwritten signature based on the empirical mode decomposition (EMD). After extracting each of the signature coordinates, a phase of preprocessing and normalisation is carried out. Then, the features of the signatures are extracted by using the EMD. After that, three similarity measures are used to match the signatures between them. The database used in our work is the one used in SVC (2004). Experimental results confirm the effectiveness of our approach and show the level of its reliability. Finally, the proposed method gives an EER of 2.03% and allows high rates of recognition compared to other approaches.

Online publication date: Thu, 02-Jan-2020

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