Please use this identifier to cite or link to this item: https://hdl.handle.net/10356/81594
Title: A Color Channel Fusion Approach for Face Recognition
Authors: Lu, Ze
Jiang, Xudong
Kot, Alex Chichung
Keywords: Color face recognition
Dimension reduction
Channel fusion
Issue Date: 2015
Source: Lu, Z., Jiang, X., & Kot, A. C. (2015). A Color Channel Fusion Approach for Face Recognition. IEEE Signal Processing Letters, 22(11), 1839-1843.
Series/Report no.: IEEE Signal Processing Letters
Abstract: Due to high dimensionality of images or generated color features, different color channels are usually processed separately and then concatenated together into a feature vector for classification. This makes channel fusion a crucial step in color FR systems. However, existing methods simply concatenate channel-wise color features without identifying the importance or reliability of features in different color channels. In this paper, we propose a color channel fusion (CCF) approach using jointly dimension reduction algorithms to select more features from reliable and discriminative channels. Experiments using two different dimension reduction approaches, two different types of features on 3 image datasets show that CCF achieves consistently better performance than color channel concatenation (CCC) method which deals with different color channels equally.
URI: https://hdl.handle.net/10356/81594
http://hdl.handle.net/10220/39558
ISSN: 1070-9908
DOI: http://dx.doi.org/10.1109/LSP.2015.2438024
Rights: © 2015 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works. The published version is available at: [http://dx.doi.org/10.1109/LSP.2015.2438024].
metadata.item.grantfulltext: open
metadata.item.fulltext: With Fulltext
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