NDLI: Application of MEEMD in post-processing of dimensionality reduction methods for face recognition

Content Provider	IET Digital Library
Author	Abbad, Abdelghafour Elharrouss, Omar Abbad, Khalid Tairi, Hamid
Abstract	Dimensionality reduction techniques are powerful tools for face recognition, because they obtain important information from a dataset. Several dimensionality reduction methods proposed in literature have been improved thanks to pre-processing approaches. However, they also require post-processing to rectify and increase the quality of projected data. This study presents a simple and new discriminative post-processing framework to make the dimensionality reduction methods robust to outliers. In detail, the proposed approach separates features according to their scale using multidimensional ensemble empirical mode decomposition (MEEMD) and then the spatial and frequency domain processing methods are employed to preserve crucial features. The performance of the proposed method is evaluated on ORL, Extended Yale B, AR, and LFW datasets by several dimensionality reduction techniques. The experimental results demonstrate that the proposed algorithm can perform very well in face recognition.
Starting Page	59
Ending Page	68
Page Count	10
ISSN	20474938
Volume Number	8
e-ISSN	20474946
Issue Number	Issue 1, Jan (2019)
Alternate Webpage(s)	https://digital-library.theiet.org/content/journals/iet-bmt/8/1
Alternate Webpage(s)	https://digital-library.theiet.org/content/journals/10.1049/iet-bmt.2018.5033
Journal	IET Biometrics
Publisher Date	2018-07-30
Access Restriction	Open
Rights Holder	© The Institution of Engineering and Technology
Subject Keyword	Computer Vision And Image Processing Technique Data Handling Technique Data Reduction Dimensionality Reduction Method Dimensionality Reduction Technique Discriminative Post-processing Framework Extended Yale B Face Recognition Feature Extraction Frequency Domain Analysis Frequency Domain Processing Method Image Recognition LFW Datasets Mathematical Analysis MEEMD Multidimensional Ensemble Empirical Mode Decomposition ORL Pre-processing Approach Spatial Domain Processing Framework
Content Type	Text
Resource Type	Article
Subject	Signal Processing Computer Vision and Pattern Recognition Software

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