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Quaternion decomposition based discriminant analysis for color face recognition
Lan R.; Zhou Y.
2017-02-06
Conference NameIEEE International Conference on Systems, Man, and Cybernetics (SMC)
Source Publication2016 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2016 - Conference Proceedings
Pages1833-1837
Conference DateOCT 09-12, 2016
Conference PlaceBudapest, HUNGARY
Abstract

In this paper, we propose a novel quaternion decomposition based discriminant analysis (QDDA) method for color face recognition. Unlike traditional approaches that handle color face images by vector representation or by each color channel individually, QDDA makes use of the quaternion to encode all color channels such that we can process all these channels in a holistic way and consider their relations simultaneously. In order to extract more discriminant color information from the image, a decomposition operation is performed to the quaternion matrix. A linear discriminant analysis is finally implemented to the obtained subcomponents for feature extraction. Experimental results have demonstrated the effectiveness of QDDA by comparing with other quaternion based methods.

DOIhttp://doi.org/10.1109/SMC.2016.7844504
URLView the original
Indexed BySCI
Language英语
WOS Research AreaComputer Science
WOS SubjectComputer Science, Cybernetics ; Computer Science, Information Systems
WOS IDWOS:000402634701125
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Document TypeConference paper
CollectionFaculty of Science and Technology
DEPARTMENT OF COMPUTER AND INFORMATION SCIENCE
AffiliationUniversidade de Macau
Recommended Citation
GB/T 7714
Lan R.,Zhou Y.. Quaternion decomposition based discriminant analysis for color face recognition[C],2017:1833-1837.
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