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Proceedings Paper

Hiding phase-quantized biometrics: a case of steganography for reduced-complexity correlation filter classifiers
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Paper Abstract

This paper introduces an application of steganography for hiding cancelable biometric data based on quad-phase correlation filter classification. The proposed technique can perform two tasks: (1) embed an encrypted (cancelable) template for biometric recognition into a host image or (2) embed the biometric data required for remote (or later) classification, such as embedding a transformed face image into the host image, so that it can be transmitted for remote authentication or stored for later use. The novel approach is that we will encode Fourier information of the template (or biometric) in the spatial representation of the host image. More importantly we show that we only need two bits per pixel in the frequency domain to represent the filter and biometric, making it compact and ideal for application of data hiding. To preserve the template (or biometric) from vulnerabilities to successful attacks, we encrypt the filter or biometric image by convolving it with a random kernel which produces an image in the spatial domain that resembles white noise, thus essentially both the frequency and spatial representation will have no visible exploitable structure. We also present results on reduced complexity correlation filter classification performance when using biometric images recovered from stego-images.

Paper Details

Date Published: 21 March 2005
PDF: 9 pages
Proc. SPIE 5681, Security, Steganography, and Watermarking of Multimedia Contents VII, (21 March 2005); doi: 10.1117/12.589404
Show Author Affiliations
Pablo Hennings, Carnegie Mellon Univ. (United States)
Marios Savvides, Carnegie Mellon Univ. (United States)
B.V.K. Vijaya Kumar, Carnegie Mellon Univ. (United States)


Published in SPIE Proceedings Vol. 5681:
Security, Steganography, and Watermarking of Multimedia Contents VII
Edward J. Delp; Ping W. Wong, Editor(s)

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