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Integrating Image Quality in 2ν-SVM Biometric Match Score Fusion

NCJ Number
305874
Journal
International Journal of Neural Systems Volume: 17 Issue: 05 Dated: 2007 Pages: 343-351
Date Published
2007
Length
11 pages
Annotation

This paper proposes an intelligent 2ν-support vector machine-based match score fusion algorithm to improve the performance of face and iris recognition by integrating the quality of images.

Abstract

The proposed algorithm applies redundant discrete wavelet transform to evaluate the underlying linear and non-linear features present in the image. A composite quality score is computed to determine the extent of smoothness, sharpness, noise, and other pertinent features present in each sub-band of the image. The match score and the corresponding quality score of an image are fused using 2ν-support vector machine to improve the verification performance. The proposed algorithm is experimentally validated using the FERET face database and the CASIA iris database. The verification performance and statistical evaluation show that the proposed algorithm outperforms existing fusion algorithms. (Published Abstract Provided)

Date Published: January 1, 2007