Affiliated with RCfalse
Multi-feature fusion using collaborative residual for hyperspectral palmprint recognition
Zhao,Shuping; Nie,Wei; Zhang,Bob
Conference Name2018 IEEE 4th International Conference on Computer and Communications (ICCC)
Source Publication2018 IEEE 4th International Conference on Computer and Communications, ICCC 2018
Conference Date7-10 Dec. 2018
Conference PlaceChengdu, China

Recently, hyperspectral imaging has attracted more and more considerable research attention because of its discriminative information. This paper presents a multiple feature fusion strategy for hyperspectral palmprint recognition, combining texture LBP feature, direction LDP feature and global deep convolutional feature (DCNN). Compared to single patterns, the proposed method is focused on the combined use to improve the distinguishability. The LBP, LDP and DCNN are applied to the hyperspectral palmprint images (of an individual) in order to extract its features forming three feature matrixes. Each matrix contains redundant information and long dimensions. Thus, the 2D-PCA is applied to reduce the dimension of every feature matrix and generates a uniform feature vector. At last, residuals of each patterns based on the collaborative representation between the test data and training data are fused. The collaborative residual of the three patterns is exploited on final recognition. The proposed methodology was experimented on a large hyperspectral palmprint dataset consisting of 53 spectral bands obtaining an EER of 0.11% and an accuracy of 99.76% at recognition.

KeywordCollaborative Residual Hyperspectral Palmprint Recognition Multiple Feature Fusion
URLView the original
Scopus ID2-s2.0-85070794024
Fulltext Access
Citation statistics
Document TypeConference paper
CollectionUniversity of Macau
Corresponding AuthorZhao,Shuping; Nie,Wei; Zhang,Bob
AffiliationDepartment of Computer and Information Science,University of Macau,Macao
First Author AffilicationUniversity of Macau
Corresponding Author AffilicationUniversity of Macau
Recommended Citation
GB/T 7714
Zhao,Shuping,Nie,Wei,Zhang,Bob. Multi-feature fusion using collaborative residual for hyperspectral palmprint recognition[C],2018:1402-1406.
Files in This Item:
There are no files associated with this item.
Related Services
Recommend this item
Usage statistics
Export to Endnote
Google Scholar
Similar articles in Google Scholar
[Zhao,Shuping]'s Articles
[Nie,Wei]'s Articles
[Zhang,Bob]'s Articles
Baidu academic
Similar articles in Baidu academic
[Zhao,Shuping]'s Articles
[Nie,Wei]'s Articles
[Zhang,Bob]'s Articles
Bing Scholar
Similar articles in Bing Scholar
[Zhao,Shuping]'s Articles
[Nie,Wei]'s Articles
[Zhang,Bob]'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.