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Proceedings Paper

Super-resolution for high magnification face images
Author(s): Yi Yao; Besma Abidi; Nathan D. Kalka; Natalia Schmid; Mongi Abidi
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Paper Abstract

Most existing face recognition algorithms require face images with a minimum resolution. Meanwhile, the rapidly emerging need for near-ground long range surveillance calls for a migration in face recognition from close-up distances to long distances and accordingly from low and constant resolution to high and adjustable resolution. With limited optical zoom capability restricted by the system hardware configuration, super-resolution (SR) provides a promising solution with no additional hardware requirements. In this paper, a brief review of existing SR algorithms is conducted and their capability of improving face recognition rates (FRR) for long range face images is studied. Algorithms applicable to real-time scenarios are implemented and their performances in terms of FRR are examined using the IRISLRHM face database [1]. Our experimental results show that SR followed by appropriate enhancement, such as wavelet based processing, is able to achieve comparable FRR when equivalent optical zoom is employed.

Paper Details

Date Published: 12 April 2007
PDF: 10 pages
Proc. SPIE 6539, Biometric Technology for Human Identification IV, 65390G (12 April 2007); doi: 10.1117/12.720113
Show Author Affiliations
Yi Yao, The Univ. of Tennessee (United States)
Besma Abidi, The Univ. of Tennessee (United States)
Nathan D. Kalka, West Virginia Univ. (United States)
Natalia Schmid, West Virginia Univ. (United States)
Mongi Abidi, The Univ. of Tennessee (United States)

Published in SPIE Proceedings Vol. 6539:
Biometric Technology for Human Identification IV
Salil Prabhakar; Arun A. Ross, Editor(s)

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