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2016 | OriginalPaper | Buchkapitel

Log-Gabor Transforms and Score Fusion to Overcome Variations in Appearance for Face Recognition

verfasst von : Mithat C̨aǧri Yildiz, Omid Sharifi, Maryam Eskandari

Erschienen in: Computer Vision and Graphics

Verlag: Springer International Publishing

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Abstract

In this paper a new hybrid scheme for overcoming variations in facial images based on the score fusion strategy is considered. The scheme takes into account Log-Gabor transform to extract facial features. The implemented scheme applies Backtracking Search Algorithm (BSA) as a novel feature selection method and Linear Discriminant Analysis (LDA) as a feature transformation method to reduce the number of features and computational cost. Then Weighted Sum Rule (WS) fusion technique is applied to fuse the produced scores for our face recognition system. The robustness of schemes is tested using FERET and ORL database. Experimental results show a significant improvement of proposed scheme over implemented methods in this study.

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Nächstes Kapitel Optimization of Numerical Calculations of Geometric Features of a Curve Describing Preprocessed X-Ray Images of Bones as a Starting Point for Syntactic Analysis of Finger Bone Contours

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Titel: Log-Gabor Transforms and Score Fusion to Overcome Variations in Appearance for Face Recognition
verfasst von: Mithat C̨aǧri Yildiz
Omid Sharifi
Maryam Eskandari
Verlag: Springer International Publishing
Buch: Computer Vision and Graphics
Print ISBN: 978-3-319-46417-6

Electronic ISBN: 978-3-319-46418-3

Copyright-Jahr: 2016
DOI: https://doi.org/10.1007/978-3-319-46418-3_31

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