Support Vector Machines (SVM)-based biometric watermarking for offline handwritten signature

Cheng-Yaw, Low and Andrew Beng-Jin, Teoh and Connie, Tee (2008) Support Vector Machines (SVM)-based biometric watermarking for offline handwritten signature. In: 3rd IEEE Conference on Industrial Electronics and Applications (ICIEA 2008) , 03-05 June 2008, Singapore, SINGAPORE.

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Abstract

Biometric watermarking refers to the incorporation of biometrics and watermarking technology. In this paper, we present a novel biometric watermarking scheme to embed handwritten signature in the host as a notice of legitimate ownership. The core of the proposed method is the synergistic integration of a statistical classifier, i.e. the Support Vector Machine, with biometric watermarking to precisely extract the signature code from the host. We abbreviate the proposed method as SVM-BW. The performance of SVM-BW is validated against simulated frequency and geometric attacks, which include JPG compression, low pass filtering, median filtering, noise addition, scaling, rotation and cropping. Experiment results reveal that SVM-BW is able to endure severe degradation on the host fidelity. Furthermore, SVM-BW shows remarkable robustness even if the host is deliberately distorted.

Item Type: Conference or Workshop Item (Lecture)
Subjects: T Technology > T Technology (General)
Q Science > QA Mathematics > QA75.5-76.95 Electronic computers. Computer science
Divisions: Faculty of Engineering and Technology (FET)
Depositing User: Ms Suzilawati Abu Samah
Date Deposited: 19 Sep 2011 07:54
Last Modified: 19 Sep 2011 07:54
URI: http://shdl.mmu.edu.my/id/eprint/2827

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