UM
Multi-scale gradient invariant for face recognition under varying illumination
Xu B.; Tang Y.Y.; Fang B.; Shang Z.W.
2012-12-01
Source PublicationInternational Journal of Pattern Recognition and Artificial Intelligence
ISSN02180014
Volume26Issue:8
AbstractIn this paper, a novel approach derived from image gradient domain called multi-scale gradient faces (MGF) is proposed to abstract multi-scale illumination-insensitive measure for face recognition. MGF applies multi-scale analysis on image gradient information, which can discover underlying inherent structure in images and keep the details at most while removing varying lighting. The proposed approach provides state-of-the-art performance on Extended YaleB and PIE: Recognition rates of 99.11% achieved on PIE database and 99.38% achieved on YaleB which outperforms most existing approaches. Furthermore, the experimental results on noised Yale-B validate that MGF is more robust to image noise. © World Scientific Publishing Company.
KeywordFace recognition illumination-insensitive measure multi-scale
DOI10.1142/S0218001412560162
URLView the original
Language英語
Fulltext Access
Citation statistics
Cited Times [WOS]:4   [WOS Record]     [Related Records in WOS]
Document TypeJournal article
CollectionUniversity of Macau
AffiliationChongqing University
Recommended Citation
GB/T 7714
Xu B.,Tang Y.Y.,Fang B.,et al. Multi-scale gradient invariant for face recognition under varying illumination[J]. International Journal of Pattern Recognition and Artificial Intelligence,2012,26(8).
APA Xu B.,Tang Y.Y.,Fang B.,&Shang Z.W..(2012).Multi-scale gradient invariant for face recognition under varying illumination.International Journal of Pattern Recognition and Artificial Intelligence,26(8).
MLA Xu B.,et al."Multi-scale gradient invariant for face recognition under varying illumination".International Journal of Pattern Recognition and Artificial Intelligence 26.8(2012).
Files in This Item:
There are no files associated with this item.
Related Services
Recommend this item
Bookmark
Usage statistics
Export to Endnote
Google Scholar
Similar articles in Google Scholar
[Xu B.]'s Articles
[Tang Y.Y.]'s Articles
[Fang B.]'s Articles
Baidu academic
Similar articles in Baidu academic
[Xu B.]'s Articles
[Tang Y.Y.]'s Articles
[Fang B.]'s Articles
Bing Scholar
Similar articles in Bing Scholar
[Xu B.]'s Articles
[Tang Y.Y.]'s Articles
[Fang B.]'s Articles
Terms of Use
No data!
Social Bookmark/Share
All comments (0)
No comment.
 

Items in the repository are protected by copyright, with all rights reserved, unless otherwise indicated.