Michiel van der Veen

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This paper considers generating binary feature vectors from biometric face data such that their privacy can be protected using recently introduced helper data systems. We explain how the binary feature vectors can be derived and investigate their statistical properties. Experimental results for a subset of the FERET and Caltech databases show that their is(More)
In this paper we apply template protection to an authenti-cation system based on 3D face data in order to protect the privacy of its users. We use the template protection system based on the helper data system (HDS). The experimental results performed on the FRGC v2.0 database demonstrate that the performance of the protected system is of the same order as(More)
1. Abstract In recent literature, privacy protection technologies for biometric templates were proposed. Among these is the so-called helper-data system (HDS) based on reliable component selection. In this paper we integrate this approach with face biometrics such that we achieve a system in which the templates are privacy protected, and multiple templates(More)
Based on existing technology used in image and video watermarking, we have developed a robust audio watermarking technique. The embedding algorithm operates in frequency domain, where the magnitudes of the Fourier coefficients are slightly modified. In the temporal domain, an additional scale parameter and gain function are necessary to refine the watermark(More)
2D Face images are traditionally used in civil governmental applications. An extension from 2D to 3D images will lead to several advantages when setting up automated authentication systems. However, privacy concerns of storing face images on smart cards or in databases will inhibit the acceptance of such systems. In this paper we concentrate on privacy(More)