Paper
12 April 2007 Super-resolution for high magnification face images
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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.
© (2007) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Yi Yao, Besma Abidi, Nathan D. Kalka, Natalia Schmid, and Mongi Abidi "Super-resolution for high magnification face images", Proc. SPIE 6539, Biometric Technology for Human Identification IV, 65390G (12 April 2007); https://doi.org/10.1117/12.720113
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Cited by 6 scholarly publications.
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KEYWORDS
Image processing

Image resolution

Facial recognition systems

Super resolution

Detection and tracking algorithms

Databases

Wavelets

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