bibtype J - Journal Article
ARLID 0444205
utime 20240103210107.7
mtime 20150528235959.9
WOS 000356732600015
SCOPUS 84930077387
DOI 10.1016/j.ins.2015.04.030
title (primary) (eng) Near infrared face recognition using Zernike moments and Hermite kernels
specification
page_count 12 s.
media_type P
serial
ARLID cav_un_epca*0256752
ISSN 0020-0255
title Information Sciences
volume_id 316
volume 1 (2015)
page_num 234-245
publisher
name Elsevier
keyword face recognition
keyword Zernike moments
keyword Hermite kernel
keyword Decision fusion
keyword Near infrared
author (primary)
ARLID cav_un_auth*0317051
name1 Farokhi
name2 Sajad
full_dept (cz) Zpracování obrazové informace
full_dept (eng) Department of Image Processing
department (cz) ZOI
department (eng) ZOI
institution UTIA-B
full_dept Department of Image Processing
fullinstit Ústav teorie informace a automatizace AV ČR, v. v. i.
author
ARLID cav_un_auth*0302105
name1 Sheikh
name2 U.U.
country MY
author
ARLID cav_un_auth*0101087
name1 Flusser
name2 Jan
full_dept (cz) Zpracování obrazové informace
full_dept Department of Image Processing
department (cz) ZOI
department ZOI
institution UTIA-B
full_dept Department of Image Processing
fullinstit Ústav teorie informace a automatizace AV ČR, v. v. i.
author
ARLID cav_un_auth*0292817
name1 Yang
name2 Bo
full_dept (cz) Zpracování obrazové informace
full_dept Department of Image Processing
department (cz) ZOI
department ZOI
institution UTIA-B
fullinstit Ústav teorie informace a automatizace AV ČR, v. v. i.
source
url http://library.utia.cas.cz/separaty/2015/ZOI/flusser-0444205.pdf
cas_special
project
project_id GA13-29225S
agency GA ČR
country CZ
ARLID cav_un_auth*0292734
abstract (eng) This work proposes a novel face recognition method based on Zernike moments (ZMs) and Hermite kernels (HKs) to cope with variations in facial expression, changes in head pose and scale, occlusions due to wearing eyeglasses and the effects of time lapse. Near infrared images are used to tackle the impact of illumination changes on face recognition, and a combination of global and local features is utilized in the decision fusion step. In the global part, ZMs are used as a feature extractor and in the local part, the images are partitioned into multiple patches and filtered patch-wise with HKs. Finally, principal component analysis followed by linear discriminant analysis is applied to data vectors to generate salient features and decision fusion is applied on the feature vectors to properly combine both global and local features. Experimental results on CASIA NIR and PolyU NIR face databases clearly show that the proposed method achieves significantly higher face recognition accuracy compared with existing methods.
reportyear 2016
RIV JD
num_of_auth 4
mrcbC52 4 A hod 4ah 20231122140952.5
permalink http://hdl.handle.net/11104/0246858
mrcbC64 1 Department of Image Processing UTIA-B 10200 COMPUTER SCIENCE, THEORY & METHODS
confidential S
mrcbT16-e COMPUTERSCIENCEINFORMATIONSYSTEMS
mrcbT16-j 0.943
mrcbT16-s 1.960
mrcbT16-4 Q1
mrcbT16-B 80.228
mrcbT16-C 94.792
mrcbT16-D Q1
mrcbT16-E Q1
arlyear 2015
mrcbTft \nSoubory v repozitáři: flusser-0444205.pdf
mrcbU14 84930077387 SCOPUS
mrcbU34 000356732600015 WOS
mrcbU63 cav_un_epca*0256752 Information Sciences 0020-0255 1872-6291 Roč. 316 č. 1 2015 234 245 Elsevier