Using empirical mode decomposition and Kullback-Leibler distance for online handwritten signature verification. (26th December 2019)

• Record Type: Journal Article
• Authors: Hafs, Toufik; Bennacer, Layachi; Brahmia, Hanene; Boughazi, Mohamed; Nait-Ali, Amine
• Is Part Of: International journal of applied pattern recognition. Volume 6:Number 1(2019)
• Page Start: 15
• Page End: 29
• Publication Date: 2019-12-26
• Subjects: online signature -- verification -- biometrics -- Kullback-Leibler divergence -- empirical mode decomposition -- EMD -- Hilbert transform -- HT; Pattern perception -- Periodicals; Pattern recognition systems -- Periodicals; 006.405
• Languages: English
• ISSNs: 2049-887X

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.