
Proceedings Paper
Quality based approach for adaptive face recognitionFormat | Member Price | Non-Member Price |
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Paper Abstract
Recent advances in biometric technology have pushed towards more robust and reliable systems. We aim to build
systems that have low recognition errors and are less affected by variation in recording conditions. Recognition errors are
often attributed to the usage of low quality biometric samples. Hence, there is a need to develop new intelligent
techniques and strategies to automatically measure/quantify the quality of biometric image samples and if necessary
restore image quality according to the need of the intended application. In this paper, we present no-reference image
quality measures in the spatial domain that have impact on face recognition. The first is called symmetrical adaptive
local quality index (SALQI) and the second is called middle halve (MH). Also, an adaptive strategy has been developed
to select the best way to restore the image quality, called symmetrical adaptive histogram equalization (SAHE). The
main benefits of using quality measures for adaptive strategy are: (1) avoidance of excessive unnecessary enhancement
procedures that may cause undesired artifacts, and (2) reduced computational complexity which is essential for real time
applications. We test the success of the proposed measures and adaptive approach for a wavelet-based face recognition
system that uses the nearest neighborhood classifier. We shall demonstrate noticeable improvements in the performance
of adaptive face recognition system over the corresponding non-adaptive scheme.
Paper Details
Date Published: 4 May 2009
PDF: 10 pages
Proc. SPIE 7351, Mobile Multimedia/Image Processing, Security, and Applications 2009, 73510N (4 May 2009); doi: 10.1117/12.817922
Published in SPIE Proceedings Vol. 7351:
Mobile Multimedia/Image Processing, Security, and Applications 2009
Sos S. Agaian; Sabah A. Jassim, Editor(s)
PDF: 10 pages
Proc. SPIE 7351, Mobile Multimedia/Image Processing, Security, and Applications 2009, 73510N (4 May 2009); doi: 10.1117/12.817922
Show Author Affiliations
Ali J. Abboud, Univ. of Buckingham (United Kingdom)
Harin Sellahewa, Univ. of Buckingham (United Kingdom)
Harin Sellahewa, Univ. of Buckingham (United Kingdom)
Sabah A. Jassim, Univ. of Buckingham (United Kingdom)
Published in SPIE Proceedings Vol. 7351:
Mobile Multimedia/Image Processing, Security, and Applications 2009
Sos S. Agaian; Sabah A. Jassim, Editor(s)
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