High-efficiency and high-accuracy digital image correlation for three-dimensional measurement

The computational efficiency and measurement accuracy of the digital image correlation (DIC) have become more and more important in recent years. For the three-dimensional DIC (3D-DIC), these issues are much more serious. First, there are two cameras employed which increases the computational amount...

Full description

Saved in:

Bibliographic Details
Published in:	Optics and lasers in engineering Vol. 65; pp. 73 - 80
Main Authors:	Gao, Yue, Cheng, Teng, Su, Yong, Xu, Xiaohai, Zhang, Yong, Zhang, Qingchuan
Format:	Journal Article
Language:	English
Published:	Elsevier Ltd 01.02.2015
Subjects:	Accuracy Algorithms Correlation analysis Deformation Digital Digital image correlation Inverse compositional Gauss–Newton algorithm Second-order shape function Shape functions Three dimensional Three-dimensional measurement Second-order shape function Inverse compositional Gauss–Newton algorithm Three-dimensional measurement Digital image correlation
ISSN:	0143-8166, 1873-0302
Online Access:	Get full text
Tags:	Add Tag No Tags, Be the first to tag this record!

Abstract	The computational efficiency and measurement accuracy of the digital image correlation (DIC) have become more and more important in recent years. For the three-dimensional DIC (3D-DIC), these issues are much more serious. First, there are two cameras employed which increases the computational amount several times. Second, because of the differences in view angles, the must-do stereo correspondence between the left and right images is equivalently a non-uniform deformation, and cannot be weakened by increasing the sampling frequency of digital cameras. This work mainly focuses on the efficiency and accuracy of 3D-DIC. The inverse compositional Gauss–Newton algorithm (IC-GN2) with the second-order shape function is firstly proposed. Because it contains the second-order displacement gradient terms, the measurement accuracy for the non-uniform deformation thus can be improved significantly, which is typically one order higher than the first-order shape function combined with the IC-GN algorithm (IC-GN1), and 2 times faster than the second-order shape function combined with the forward additive Gauss–Newton algorithm (FA-GN2). Then, based on the features of the IC-GN1 and IC-GN2 algorithms, a high-efficiency and high-accuracy measurement strategy for 3D-DIC is proposed in the end. •Inverse compositional Gauss–Newton with second-order shape function is proposed.•Simulation results show that the new algorithm has second-order precision.•Simulation results show that the new algorithm is faster than forward algorithms.•Experiment results further validate the speed and precision of the new algorithm.•The new algorithm is practical on large deformation and stereo correspondence.
AbstractList	The computational efficiency and measurement accuracy of the digital image correlation (DIC) have become more and more important in recent years. For the three-dimensional DIC (3D-DIC), these issues are much more serious. First, there are two cameras employed which increases the computational amount several times. Second, because of the differences in view angles, the must-do stereo correspondence between the left and right images is equivalently a non-uniform deformation, and cannot be weakened by increasing the sampling frequency of digital cameras. This work mainly focuses on the efficiency and accuracy of 3D-DIC. The inverse compositional Gauss-Newton algorithm (IC-GN super(2)) with the second-order shape function is firstly proposed. Because it contains the second-order displacement gradient terms, the measurement accuracy for the non-uniform deformation thus can be improved significantly, which is typically one order higher than the first-order shape function combined with the IC-GN algorithm (IC-GN super(1)), and 2 times faster than the second-order shape function combined with the forward additive Gauss-Newton algorithm (FA-GN super(2)). Then, based on the features of the IC-GN super(1) and IC-GN super(2) algorithms, a high-efficiency and high-accuracy measurement strategy for 3D-DIC is proposed in the end. The computational efficiency and measurement accuracy of the digital image correlation (DIC) have become more and more important in recent years. For the three-dimensional DIC (3D-DIC), these issues are much more serious. First, there are two cameras employed which increases the computational amount several times. Second, because of the differences in view angles, the must-do stereo correspondence between the left and right images is equivalently a non-uniform deformation, and cannot be weakened by increasing the sampling frequency of digital cameras. This work mainly focuses on the efficiency and accuracy of 3D-DIC. The inverse compositional Gauss–Newton algorithm (IC-GN2) with the second-order shape function is firstly proposed. Because it contains the second-order displacement gradient terms, the measurement accuracy for the non-uniform deformation thus can be improved significantly, which is typically one order higher than the first-order shape function combined with the IC-GN algorithm (IC-GN1), and 2 times faster than the second-order shape function combined with the forward additive Gauss–Newton algorithm (FA-GN2). Then, based on the features of the IC-GN1 and IC-GN2 algorithms, a high-efficiency and high-accuracy measurement strategy for 3D-DIC is proposed in the end. •Inverse compositional Gauss–Newton with second-order shape function is proposed.•Simulation results show that the new algorithm has second-order precision.•Simulation results show that the new algorithm is faster than forward algorithms.•Experiment results further validate the speed and precision of the new algorithm.•The new algorithm is practical on large deformation and stereo correspondence.
Author	Su, Yong Xu, Xiaohai Zhang, Qingchuan Cheng, Teng Gao, Yue Zhang, Yong
Author_xml	– sequence: 1 givenname: Yue surname: Gao fullname: Gao, Yue – sequence: 2 givenname: Teng surname: Cheng fullname: Cheng, Teng email: chteng@ustc.edu.cn – sequence: 3 givenname: Yong surname: Su fullname: Su, Yong – sequence: 4 givenname: Xiaohai surname: Xu fullname: Xu, Xiaohai – sequence: 5 givenname: Yong surname: Zhang fullname: Zhang, Yong – sequence: 6 givenname: Qingchuan surname: Zhang fullname: Zhang, Qingchuan email: zhangqc@ustc.edu.cn
BookMark	eNqNkLFOwzAQhi1UJNrCM5CRJcF2HMcdGKoKKFIlFhiR5diX1lUaF9tB6tvjUsTAAtNJ__3fSfdN0Kh3PSB0TXBBMOG328LtY6cC9OuCYsIKXBWYlGdoTERd5rjEdITGaVHmgnB-gSYhbHEiGSFj9La0600ObWu1hV4fMtWbbHPMlNaDVykxdm2j6jK7U2vItPMeOhWt67PW-SxuPEBu7A76kLLU24EKg4cUxEt03qouwNX3nKLXh_uXxTJfPT8-LearXDPBYs4rTStRc6yEpi3jQqu6npmWVYbXpuHCNDPTMCNYyWmDKaVKGI6B8lY3daXKKbo53d179z5AiHJng4auUz24IUjCK8IYrmqRqnenqvYuBA-t1Om74zvRK9tJguVRq9zKH63yqFXiSiatia9_8XufzPjDP8j5iYRk4sOCl-HLORjrQUdpnP3zxieV7JvJ
CitedBy_id	crossref_primary_10_1109_ACCESS_2018_2843725 crossref_primary_10_1080_25740881_2019_1695273 crossref_primary_10_1016_j_measurement_2023_112567 crossref_primary_10_1364_AO_380322 crossref_primary_10_1016_j_optlaseng_2022_107234 crossref_primary_10_1088_2515_7647_abcbe4 crossref_primary_10_1016_j_optlaseng_2024_108568 crossref_primary_10_3390_s17122782 crossref_primary_10_1016_j_optlaseng_2023_107879 crossref_primary_10_3389_fmats_2020_598973 crossref_primary_10_1007_s11431_017_9125_7 crossref_primary_10_1016_j_optlaseng_2021_106541 crossref_primary_10_1016_j_istruc_2025_109277 crossref_primary_10_1007_s11340_017_0274_2 crossref_primary_10_1016_j_measurement_2024_116517 crossref_primary_10_1016_j_neucom_2024_127617 crossref_primary_10_1016_j_engfracmech_2025_111262 crossref_primary_10_1016_j_optlaseng_2025_109245 crossref_primary_10_3390_s18041208 crossref_primary_10_1007_s11440_024_02275_2 crossref_primary_10_1016_j_optlaseng_2019_105942 crossref_primary_10_1007_s11340_016_0133_6 crossref_primary_10_1364_AO_54_010089 crossref_primary_10_1109_JSEN_2019_2915986 crossref_primary_10_1016_j_optlaseng_2023_107777 crossref_primary_10_1007_s00603_023_03351_x crossref_primary_10_1364_AO_57_000924 crossref_primary_10_1016_j_optlaseng_2024_108582 crossref_primary_10_1016_j_tafmec_2023_103947 crossref_primary_10_1007_s11431_019_9525_3 crossref_primary_10_1016_j_optlaseng_2018_03_029 crossref_primary_10_1016_j_ymssp_2022_109273 crossref_primary_10_1007_s11340_015_0080_7 crossref_primary_10_1016_j_ndteint_2020_102219 crossref_primary_10_3390_s25185675 crossref_primary_10_1007_s11340_015_0054_9 crossref_primary_10_1016_j_polymertesting_2019_106015 crossref_primary_10_1016_j_ymssp_2022_108980 crossref_primary_10_1007_s11340_022_00905_y crossref_primary_10_1016_j_ymssp_2021_108040 crossref_primary_10_1016_j_optcom_2022_129015 crossref_primary_10_1016_j_measurement_2018_06_022 crossref_primary_10_1016_j_optlaseng_2019_105964 crossref_primary_10_3390_s19214726 crossref_primary_10_1016_j_asoc_2017_08_011 crossref_primary_10_1007_s10409_017_0719_y crossref_primary_10_1016_j_ijsolstr_2024_112948 crossref_primary_10_1007_s11340_017_0253_7 crossref_primary_10_3390_rs12182906 crossref_primary_10_1016_j_measurement_2025_117301 crossref_primary_10_1016_j_measurement_2025_117783 crossref_primary_10_1016_j_optlaseng_2024_108362 crossref_primary_10_1364_AO_481625 crossref_primary_10_1007_s40799_025_00791_8 crossref_primary_10_1016_j_mechmat_2021_104138 crossref_primary_10_1007_s11431_022_2122_y crossref_primary_10_1016_j_optlaseng_2024_108250 crossref_primary_10_3390_en17071566 crossref_primary_10_1016_j_polymertesting_2019_106111 crossref_primary_10_1088_1361_6501_ab1c9c crossref_primary_10_1016_j_optlastec_2025_112958 crossref_primary_10_1016_j_jnucmat_2020_152565 crossref_primary_10_1016_j_optlaseng_2016_09_010 crossref_primary_10_1016_j_optlastec_2024_112177 crossref_primary_10_1016_j_optlaseng_2016_09_011 crossref_primary_10_1016_j_engstruct_2020_110551 crossref_primary_10_1016_j_jmst_2020_02_001 crossref_primary_10_3390_app11114904 crossref_primary_10_1088_1361_6501_adb5ad crossref_primary_10_1088_1361_6501_aaf846 crossref_primary_10_1016_j_compstruct_2019_01_024 crossref_primary_10_1109_ACCESS_2021_3068467 crossref_primary_10_1177_0309324716668674 crossref_primary_10_1016_j_measurement_2024_115617 crossref_primary_10_1520_JTE20230485 crossref_primary_10_1007_s10409_024_23464_x crossref_primary_10_1088_1361_6501_aac55b crossref_primary_10_1016_j_cja_2024_02_003 crossref_primary_10_3389_fbuil_2019_00085 crossref_primary_10_1109_TIM_2021_3065436 crossref_primary_10_1016_j_optlaseng_2014_12_010 crossref_primary_10_1016_j_optlaseng_2024_108267 crossref_primary_10_1016_j_optlaseng_2015_03_001 crossref_primary_10_1016_j_taml_2016_04_003 crossref_primary_10_3390_s23063317 crossref_primary_10_1016_j_engstruct_2022_113998 crossref_primary_10_1088_1361_6501_aaa940 crossref_primary_10_1016_j_measurement_2021_109999 crossref_primary_10_1016_j_optlaseng_2023_107566 crossref_primary_10_1016_j_polymertesting_2018_12_001 crossref_primary_10_1016_j_optlaseng_2018_10_012 crossref_primary_10_1016_j_tafmec_2025_104884 crossref_primary_10_1016_j_ijmecsci_2020_106002 crossref_primary_10_1016_j_optlaseng_2016_05_019 crossref_primary_10_1007_s00264_017_3728_3 crossref_primary_10_1016_j_optlaseng_2015_03_005 crossref_primary_10_1007_s11340_016_0138_1 crossref_primary_10_1111_str_12315 crossref_primary_10_1364_AO_405551 crossref_primary_10_3390_jmse12111955 crossref_primary_10_1016_j_optlaseng_2016_08_016 crossref_primary_10_1007_s11340_021_00790_x crossref_primary_10_1016_j_engstruct_2023_117416 crossref_primary_10_1007_s11340_017_0294_y crossref_primary_10_1109_JSEN_2017_2786747 crossref_primary_10_1007_s11340_016_0180_z crossref_primary_10_1007_s00170_019_03717_y crossref_primary_10_1016_j_measurement_2020_108618 crossref_primary_10_3390_met6050120 crossref_primary_10_1117_1_OE_61_7_070901 crossref_primary_10_1016_j_optlaseng_2017_06_019 crossref_primary_10_1088_1361_6501_aa70f8 crossref_primary_10_1016_j_cemconcomp_2025_106012 crossref_primary_10_1016_j_optlaseng_2018_08_022 crossref_primary_10_1088_1361_6501_acb2e2 crossref_primary_10_1016_j_optlaseng_2017_06_010 crossref_primary_10_1088_1361_6501_ac7a06 crossref_primary_10_1016_j_optlaseng_2021_106812 crossref_primary_10_1016_j_optlaseng_2021_106930 crossref_primary_10_1016_j_culher_2022_11_007 crossref_primary_10_1088_0957_0233_27_12_125010 crossref_primary_10_1007_s12274_021_3357_4 crossref_primary_10_1016_j_optlaseng_2016_01_007 crossref_primary_10_1007_s11340_024_01079_5 crossref_primary_10_1007_s11340_020_00588_3 crossref_primary_10_3390_f13101627 crossref_primary_10_3390_s20123530 crossref_primary_10_1016_j_ijleo_2023_170901 crossref_primary_10_1016_j_optlaseng_2016_01_002 crossref_primary_10_1016_j_oceaneng_2022_111512 crossref_primary_10_3390_ma15217543 crossref_primary_10_1016_j_optlaseng_2024_108622 crossref_primary_10_1007_s11340_025_01183_0 crossref_primary_10_1016_j_ymssp_2024_111792 crossref_primary_10_1088_1361_6501_ab3c80 crossref_primary_10_1016_j_optlaseng_2024_108070 crossref_primary_10_1016_j_heliyon_2024_e37782 crossref_primary_10_1016_j_optlaseng_2021_106905 crossref_primary_10_1017_jfm_2021_403 crossref_primary_10_3139_120_111406 crossref_primary_10_1016_j_measurement_2024_115809 crossref_primary_10_1088_1361_6501_ad7971 crossref_primary_10_1177_14759217231172297 crossref_primary_10_1016_j_optlaseng_2018_05_016 crossref_primary_10_1007_s11340_021_00714_9 crossref_primary_10_1109_ACCESS_2024_3398786 crossref_primary_10_1016_j_optlaseng_2018_07_013 crossref_primary_10_1007_s11340_017_0268_0 crossref_primary_10_1016_j_optlaseng_2017_09_020 crossref_primary_10_1016_j_optlaseng_2024_108405 crossref_primary_10_1364_AO_387678 crossref_primary_10_3788_AOSOL250476 crossref_primary_10_1016_j_measurement_2021_110212 crossref_primary_10_1088_1361_6501_acda53 crossref_primary_10_1364_AO_529326 crossref_primary_10_1016_j_optlaseng_2021_106743 crossref_primary_10_1109_ACCESS_2020_3017236 crossref_primary_10_1109_JSEN_2021_3054805 crossref_primary_10_1016_j_compgeo_2023_106027 crossref_primary_10_1109_TIM_2025_3593568 crossref_primary_10_1016_j_optlaseng_2017_05_010 crossref_primary_10_1364_AO_55_007186 crossref_primary_10_1088_0957_0233_26_4_045202 crossref_primary_10_1007_s12559_014_9313_9 crossref_primary_10_1016_j_jnucmat_2020_151992 crossref_primary_10_3390_s22249766 crossref_primary_10_1016_j_polymertesting_2024_108377 crossref_primary_10_1016_j_optlaseng_2024_108651 crossref_primary_10_1088_1361_6501_adbbc8 crossref_primary_10_1016_j_cemconcomp_2017_11_005 crossref_primary_10_1016_j_optlaseng_2017_05_018 crossref_primary_10_1016_j_optlaseng_2020_106510 crossref_primary_10_1088_1742_6596_2468_1_012121 crossref_primary_10_1007_s11440_018_0676_z crossref_primary_10_3390_app13032019 crossref_primary_10_1016_j_optlaseng_2019_04_023 crossref_primary_10_1016_j_measurement_2023_112549 crossref_primary_10_1016_j_tust_2023_105154 crossref_primary_10_3390_ma16083137 crossref_primary_10_1016_j_ultramic_2024_113924 crossref_primary_10_1109_TIM_2024_3463020 crossref_primary_10_1016_j_ymssp_2021_108072 crossref_primary_10_1016_j_optlaseng_2019_03_018 crossref_primary_10_1016_j_optlaseng_2025_108981 crossref_primary_10_1111_str_12469 crossref_primary_10_1016_j_measurement_2023_113760 crossref_primary_10_1155_2021_5583355 crossref_primary_10_1016_j_ijsolstr_2018_03_030 crossref_primary_10_1016_j_optlaseng_2020_106097 crossref_primary_10_1038_s41378_024_00735_z crossref_primary_10_1016_j_optlaseng_2017_09_013 crossref_primary_10_1016_j_optlaseng_2018_12_008 crossref_primary_10_1364_AO_443878 crossref_primary_10_1016_j_optlaseng_2015_01_012 crossref_primary_10_1016_j_optlaseng_2016_07_002 crossref_primary_10_1088_1361_6501_aa7a6e crossref_primary_10_3390_s22218110
Cites_doi	10.1023/B:FRAC.0000007376.06477.e8 10.1007/BF02321649 10.1016/j.materresbull.2006.03.002 10.1016/j.ijplas.2005.03.017 10.1109/CVPR.2001.990652 10.1016/j.msea.2004.11.044 10.1016/j.optlaseng.2008.05.005 10.1111/j.1475-1305.2006.00258.x 10.1117/1.1511749 10.1016/j.measurement.2006.03.008 10.1117/1.1387992 10.1016/j.optlaseng.2007.11.009 10.1007/BF02326485 10.1016/j.optlaseng.2011.02.023 10.1007/BF02410987 10.1364/AO.45.007785 10.1364/AO.48.001535 10.1088/0957-0233/20/6/062001 10.1364/AO.49.005501 10.1088/0957-0233/21/3/035101 10.1023/B:VISI.0000011205.11775.fd 10.1007/s11340-013-9717-6 10.1007/BF02321405 10.1007/BF02325092
ContentType	Journal Article
Copyright	2014 Elsevier Ltd
Copyright_xml	– notice: 2014 Elsevier Ltd
DBID	AAYXX CITATION 7SP 7TB 7U5 8FD FR3 H8D L7M
DOI	10.1016/j.optlaseng.2014.05.013
DatabaseName	CrossRef Electronics & Communications Abstracts Mechanical & Transportation Engineering Abstracts Solid State and Superconductivity Abstracts Technology Research Database Engineering Research Database Aerospace Database Advanced Technologies Database with Aerospace
DatabaseTitle	CrossRef Aerospace Database Technology Research Database Mechanical & Transportation Engineering Abstracts Electronics & Communications Abstracts Solid State and Superconductivity Abstracts Engineering Research Database Advanced Technologies Database with Aerospace
DatabaseTitleList	Aerospace Database
DeliveryMethod	fulltext_linktorsrc
Discipline	Engineering Physics
EISSN	1873-0302
EndPage	80
ExternalDocumentID	10_1016_j_optlaseng_2014_05_013 S0143816614001493
GroupedDBID	--K --M .~1 0R~ 123 1B1 1RT 1~. 1~5 29N 4.4 457 4G. 5VS 7-5 71M 8P~ 9JN AABXZ AACTN AAEDT AAEDW AAEPC AAIAV AAIKJ AAKOC AALRI AAOAW AAQFI AAQXK AAXUO ABFNM ABJNI ABMAC ABNEU ABXDB ABXRA ABYKQ ACDAQ ACFVG ACGFS ACNNM ACRLP ADBBV ADEZE ADMUD ADTZH AEBSH AECPX AEKER AENEX AEZYN AFKWA AFRZQ AFTJW AGHFR AGUBO AGYEJ AHHHB AHJVU AIEXJ AIKHN AITUG AIVDX AJBFU AJOXV ALMA_UNASSIGNED_HOLDINGS AMFUW AMRAJ ASPBG AVWKF AXJTR AZFZN BBWZM BJAXD BKOJK BLXMC CS3 DU5 EBS EFJIC EFLBG EJD EO8 EO9 EP2 EP3 F5P FDB FEDTE FGOYB FIRID FNPLU FYGXN G-2 G-Q G8K GBLVA HMV HVGLF HZ~ IHE J1W JJJVA KOM LY7 M38 M41 MAGPM MO0 N9A NDZJH O-L O9- OAUVE OGIMB OZT P-8 P-9 P2P PC. Q38 R2- RIG RNS ROL RPZ SDF SDG SDP SES SET SEW SPC SPCBC SPD SPG SSM SSQ SST SSZ T5K VOH WUQ XPP ZMT ~02 ~G- 9DU AATTM AAXKI AAYWO AAYXX ABDPE ABWVN ACLOT ACRPL ACVFH ADCNI ADNMO AEIPS AEUPX AFJKZ AFPUW AGQPQ AIGII AIIUN AKBMS AKRWK AKYEP ANKPU APXCP CITATION EFKBS ~HD 7SP 7TB 7U5 8FD FR3 H8D L7M
ID	FETCH-LOGICAL-c484t-65c258760a8c2f468ca779df45d67db68db9db4d84362b0222a8d60e26fcb75a3
ISICitedReferencesCount	240
ISICitedReferencesURI	http://www.webofscience.com/api/gateway?GWVersion=2&SrcApp=Summon&SrcAuth=ProQuest&DestLinkType=CitingArticles&DestApp=WOS_CPL&KeyUT=000345492500010&url=https%3A%2F%2Fcvtisr.summon.serialssolutions.com%2F%23%21%2Fsearch%3Fho%3Df%26include.ft.matches%3Dt%26l%3Dnull%26q%3D
ISSN	0143-8166
IngestDate	Wed Oct 01 13:49:44 EDT 2025 Sat Nov 29 07:58:49 EST 2025 Tue Nov 18 22:11:30 EST 2025 Fri Feb 23 02:22:50 EST 2024
IsPeerReviewed	true
IsScholarly	true
Keywords	Second-order shape function Inverse compositional Gauss–Newton algorithm Three-dimensional measurement Digital image correlation
Language	English
LinkModel	OpenURL
MergedId	FETCHMERGED-LOGICAL-c484t-65c258760a8c2f468ca779df45d67db68db9db4d84362b0222a8d60e26fcb75a3
Notes	ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 23
PQID	1651440578
PQPubID	23500
PageCount	8
ParticipantIDs	proquest_miscellaneous_1651440578 crossref_citationtrail_10_1016_j_optlaseng_2014_05_013 crossref_primary_10_1016_j_optlaseng_2014_05_013 elsevier_sciencedirect_doi_10_1016_j_optlaseng_2014_05_013
PublicationCentury	2000
PublicationDate	2015-02-01
PublicationDateYYYYMMDD	2015-02-01
PublicationDate_xml	– month: 02 year: 2015 text: 2015-02-01 day: 01
PublicationDecade	2010
PublicationTitle	Optics and lasers in engineering
PublicationYear	2015
Publisher	Elsevier Ltd
Publisher_xml	– name: Elsevier Ltd
References	Pan, Li, Tong (bib21) 2013; 53 Wang, Hu, Wu (bib6) 2006; 41 Sutton, Yan, Tiwari, Schreier, Orteu (bib24) 2008; 46 B Lucas, T Kanade. An iterative image registration technique with an application to stereo vision. In: Proceedings of the international joint conference on artificial intelligence; 1981. pp. 674–679. Zhou, Goodson (bib27) 2001; 40 Kang, Zhang, Wang, Qin (bib9) 2005; 394 Zhang, Kang, Wang, Qin, Qiu, Li (bib10) 2006; 39 Bruck, McNeil, Sutton, Peters (bib17) 1989; 29 Orteu (bib23) 2009; 47 Pan, Qian, Xie, Asundi (bib22) 2009; 20 Lu, Cary (bib25) 2000; 40 Pan, Li (bib12) 2011; 49 S Baker, I Matthews. Equivalence and efficiency of image alignment algorithms. In: Proceedings of the IEEE computer society conference on computer vision and pattern recognition; 2001. pp. 1090–1097. Wang, Kang (bib7) 2002; 41 Baker, Matthews (bib20) 2004; 56 Sutton, Orteu, Schreier (bib3) 2009 Hild, Roux (bib4) 2006; 42 Yang, He, Quan (bib11) 2006; 45 Chu, Ranson, Sutton, Peters (bib2) 1985; 25 Zhang, Jiang, Jiang, Chen, Wu (bib5) 2005; 21 Huang, Zhu, Pan, Qin, Peng, Xiong (bib15) 2010; 21 Pan (bib13) 2009; 48 Vendroux, Knauss (bib14) 1998; 38 Pan, Xie, Wang (bib18) 2010; 49 Schreier, Sutton (bib26) 2002; 42 Wang, Kang, Zhang, Qin (bib8) 2003; 123 Peters, Ranson (bib1) 1981; 21 Sutton (10.1016/j.optlaseng.2014.05.013_bib24) 2008; 46 Baker (10.1016/j.optlaseng.2014.05.013_bib20) 2004; 56 Huang (10.1016/j.optlaseng.2014.05.013_bib15) 2010; 21 Zhang (10.1016/j.optlaseng.2014.05.013_bib5) 2005; 21 Chu (10.1016/j.optlaseng.2014.05.013_bib2) 1985; 25 Wang (10.1016/j.optlaseng.2014.05.013_bib7) 2002; 41 Pan (10.1016/j.optlaseng.2014.05.013_bib18) 2010; 49 Peters (10.1016/j.optlaseng.2014.05.013_bib1) 1981; 21 Yang (10.1016/j.optlaseng.2014.05.013_bib11) 2006; 45 Bruck (10.1016/j.optlaseng.2014.05.013_bib17) 1989; 29 Pan (10.1016/j.optlaseng.2014.05.013_bib13) 2009; 48 Orteu (10.1016/j.optlaseng.2014.05.013_bib23) 2009; 47 Wang (10.1016/j.optlaseng.2014.05.013_bib8) 2003; 123 Pan (10.1016/j.optlaseng.2014.05.013_bib21) 2013; 53 Hild (10.1016/j.optlaseng.2014.05.013_bib4) 2006; 42 Zhou (10.1016/j.optlaseng.2014.05.013_bib27) 2001; 40 Pan (10.1016/j.optlaseng.2014.05.013_bib12) 2011; 49 Sutton (10.1016/j.optlaseng.2014.05.013_bib3) 2009 Wang (10.1016/j.optlaseng.2014.05.013_bib6) 2006; 41 Pan (10.1016/j.optlaseng.2014.05.013_bib22) 2009; 20 Vendroux (10.1016/j.optlaseng.2014.05.013_bib14) 1998; 38 10.1016/j.optlaseng.2014.05.013_bib16 Schreier (10.1016/j.optlaseng.2014.05.013_bib26) 2002; 42 Zhang (10.1016/j.optlaseng.2014.05.013_bib10) 2006; 39 10.1016/j.optlaseng.2014.05.013_bib19 Kang (10.1016/j.optlaseng.2014.05.013_bib9) 2005; 394 Lu (10.1016/j.optlaseng.2014.05.013_bib25) 2000; 40
References_xml	– volume: 21 start-page: 427 year: 1981 end-page: 431 ident: bib1 article-title: Digital imaging techniques in experimental stress analysis publication-title: Opt Eng – volume: 25 start-page: 232 year: 1985 end-page: 244 ident: bib2 article-title: Applications of digital-image-correlation techniques to experimental mechanics publication-title: Exp Mech – volume: 49 start-page: 841 year: 2011 end-page: 847 ident: bib12 article-title: A fast digital image correlation method for deformation measurement publication-title: Opt Lasers Eng – volume: 53 start-page: 1277 year: 2013 end-page: 1289 ident: bib21 article-title: Fast, robust and accurate digital image correlation calculation without redundant computations publication-title: Exp Mech – volume: 21 start-page: 035101 year: 2010 ident: bib15 article-title: A high-efficiency digital image correlation method based on a fast recursive scheme publication-title: Meas Sci Technol – year: 2009 ident: bib3 article-title: Image correlation for shape, motion and deformation measurements – volume: 48 start-page: 1535 year: 2009 end-page: 1542 ident: bib13 article-title: Reliability-guided digital image correlation for image deformation measurement publication-title: Appl Opt – reference: S Baker, I Matthews. Equivalence and efficiency of image alignment algorithms. In: Proceedings of the IEEE computer society conference on computer vision and pattern recognition; 2001. pp. 1090–1097. – volume: 42 start-page: 69 year: 2006 end-page: 80 ident: bib4 article-title: Digital image correlation: from displacement measurement to identification of elastic properties – a review publication-title: Strain – volume: 21 start-page: 2150 year: 2005 end-page: 2173 ident: bib5 article-title: On the propagation and pulsation of Portevin-Le Chatelier deformation bands: an experimental study with digital speckle pattern metrology publication-title: Int J Plast – volume: 41 start-page: 2793 year: 2002 end-page: 2798 ident: bib7 article-title: Improved digital speckle correlation method and its application in fracture analysis of metallic foil publication-title: Opt Eng – volume: 394 start-page: 312 year: 2005 end-page: 319 ident: bib9 article-title: Experimental investigations of the effect of thickness on fracture toughness of metallic foils publication-title: Mater Sci Eng A – reference: B Lucas, T Kanade. An iterative image registration technique with an application to stereo vision. In: Proceedings of the international joint conference on artificial intelligence; 1981. pp. 674–679. – volume: 40 start-page: 393 year: 2000 end-page: 400 ident: bib25 article-title: Deformation measurements by digital image correlation: implementation of a second-order displacement gradient publication-title: Exp Mech – volume: 45 start-page: 7785 year: 2006 end-page: 7790 ident: bib11 article-title: Characterization of dynamic microgyroscopes by use of temporal digital image correlation publication-title: Appl Opt – volume: 41 start-page: 1949 year: 2006 end-page: 1958 ident: bib6 article-title: Internal microstructure evolution of aluminum foams under compression publication-title: Mater Res Bull – volume: 29 start-page: 261 year: 1989 end-page: 267 ident: bib17 article-title: Digital image correlation using Newton–Raphson method of partial differential correction publication-title: Exp Mech – volume: 123 start-page: 177 year: 2003 end-page: 185 ident: bib8 article-title: Size effect on the fracture toughness of metallic foil publication-title: Int J Fract – volume: 49 start-page: 5501 year: 2010 end-page: 5509 ident: bib18 article-title: Equivalence of digital image correlation criteria for pattern matching publication-title: Appl Opt – volume: 20 start-page: 062001 year: 2009 ident: bib22 article-title: Two-dimensional digital image correlation for in-plane displacement and strain measurement: a review publication-title: Meas Sci Technol – volume: 38 start-page: 86 year: 1998 end-page: 92 ident: bib14 article-title: Submicron deformation field measurements: Part 2. Improved digital image correlation publication-title: Exp Mech – volume: 56 start-page: 221 year: 2004 end-page: 255 ident: bib20 article-title: Lucas-Kanade 20 years on: a unifying framework publication-title: Int J Comput Vis – volume: 47 start-page: 282 year: 2009 end-page: 291 ident: bib23 article-title: 3-D computer vision in experimental mechanics publication-title: Opt Lasers Eng – volume: 40 start-page: 1613 year: 2001 end-page: 1620 ident: bib27 article-title: Subpixel displacement and deformation gradient measurement using digital image/speckle correlation (DISC) publication-title: Opt Eng – volume: 39 start-page: 710 year: 2006 end-page: 718 ident: bib10 article-title: A novel coarse-fine search scheme for digital image correlation method publication-title: Measurement – volume: 46 start-page: 746 year: 2008 end-page: 757 ident: bib24 article-title: The effect of out-of-plane motion on 2D and 3D digital image correlation measurements publication-title: Opt Lasers Eng – volume: 42 start-page: 303 year: 2002 end-page: 310 ident: bib26 article-title: Systematic errors in digital image correlation due to undermatched subset shape functions publication-title: Exp Mech – volume: 123 start-page: 177 year: 2003 ident: 10.1016/j.optlaseng.2014.05.013_bib8 article-title: Size effect on the fracture toughness of metallic foil publication-title: Int J Fract doi: 10.1023/B:FRAC.0000007376.06477.e8 – volume: 38 start-page: 86 year: 1998 ident: 10.1016/j.optlaseng.2014.05.013_bib14 article-title: Submicron deformation field measurements: Part 2. Improved digital image correlation publication-title: Exp Mech doi: 10.1007/BF02321649 – volume: 21 start-page: 427 year: 1981 ident: 10.1016/j.optlaseng.2014.05.013_bib1 article-title: Digital imaging techniques in experimental stress analysis publication-title: Opt Eng – volume: 41 start-page: 1949 year: 2006 ident: 10.1016/j.optlaseng.2014.05.013_bib6 article-title: Internal microstructure evolution of aluminum foams under compression publication-title: Mater Res Bull doi: 10.1016/j.materresbull.2006.03.002 – volume: 21 start-page: 2150 year: 2005 ident: 10.1016/j.optlaseng.2014.05.013_bib5 article-title: On the propagation and pulsation of Portevin-Le Chatelier deformation bands: an experimental study with digital speckle pattern metrology publication-title: Int J Plast doi: 10.1016/j.ijplas.2005.03.017 – ident: 10.1016/j.optlaseng.2014.05.013_bib19 doi: 10.1109/CVPR.2001.990652 – volume: 394 start-page: 312 year: 2005 ident: 10.1016/j.optlaseng.2014.05.013_bib9 article-title: Experimental investigations of the effect of thickness on fracture toughness of metallic foils publication-title: Mater Sci Eng A doi: 10.1016/j.msea.2004.11.044 – volume: 46 start-page: 746 year: 2008 ident: 10.1016/j.optlaseng.2014.05.013_bib24 article-title: The effect of out-of-plane motion on 2D and 3D digital image correlation measurements publication-title: Opt Lasers Eng doi: 10.1016/j.optlaseng.2008.05.005 – year: 2009 ident: 10.1016/j.optlaseng.2014.05.013_bib3 – volume: 42 start-page: 69 year: 2006 ident: 10.1016/j.optlaseng.2014.05.013_bib4 article-title: Digital image correlation: from displacement measurement to identification of elastic properties – a review publication-title: Strain doi: 10.1111/j.1475-1305.2006.00258.x – volume: 41 start-page: 2793 year: 2002 ident: 10.1016/j.optlaseng.2014.05.013_bib7 article-title: Improved digital speckle correlation method and its application in fracture analysis of metallic foil publication-title: Opt Eng doi: 10.1117/1.1511749 – volume: 39 start-page: 710 year: 2006 ident: 10.1016/j.optlaseng.2014.05.013_bib10 article-title: A novel coarse-fine search scheme for digital image correlation method publication-title: Measurement doi: 10.1016/j.measurement.2006.03.008 – volume: 40 start-page: 1613 year: 2001 ident: 10.1016/j.optlaseng.2014.05.013_bib27 article-title: Subpixel displacement and deformation gradient measurement using digital image/speckle correlation (DISC) publication-title: Opt Eng doi: 10.1117/1.1387992 – volume: 47 start-page: 282 year: 2009 ident: 10.1016/j.optlaseng.2014.05.013_bib23 article-title: 3-D computer vision in experimental mechanics publication-title: Opt Lasers Eng doi: 10.1016/j.optlaseng.2007.11.009 – volume: 40 start-page: 393 year: 2000 ident: 10.1016/j.optlaseng.2014.05.013_bib25 article-title: Deformation measurements by digital image correlation: implementation of a second-order displacement gradient publication-title: Exp Mech doi: 10.1007/BF02326485 – volume: 49 start-page: 841 year: 2011 ident: 10.1016/j.optlaseng.2014.05.013_bib12 article-title: A fast digital image correlation method for deformation measurement publication-title: Opt Lasers Eng doi: 10.1016/j.optlaseng.2011.02.023 – volume: 42 start-page: 303 year: 2002 ident: 10.1016/j.optlaseng.2014.05.013_bib26 article-title: Systematic errors in digital image correlation due to undermatched subset shape functions publication-title: Exp Mech doi: 10.1007/BF02410987 – volume: 45 start-page: 7785 year: 2006 ident: 10.1016/j.optlaseng.2014.05.013_bib11 article-title: Characterization of dynamic microgyroscopes by use of temporal digital image correlation publication-title: Appl Opt doi: 10.1364/AO.45.007785 – volume: 48 start-page: 1535 year: 2009 ident: 10.1016/j.optlaseng.2014.05.013_bib13 article-title: Reliability-guided digital image correlation for image deformation measurement publication-title: Appl Opt doi: 10.1364/AO.48.001535 – volume: 20 start-page: 062001 year: 2009 ident: 10.1016/j.optlaseng.2014.05.013_bib22 article-title: Two-dimensional digital image correlation for in-plane displacement and strain measurement: a review publication-title: Meas Sci Technol doi: 10.1088/0957-0233/20/6/062001 – ident: 10.1016/j.optlaseng.2014.05.013_bib16 – volume: 49 start-page: 5501 year: 2010 ident: 10.1016/j.optlaseng.2014.05.013_bib18 article-title: Equivalence of digital image correlation criteria for pattern matching publication-title: Appl Opt doi: 10.1364/AO.49.005501 – volume: 21 start-page: 035101 year: 2010 ident: 10.1016/j.optlaseng.2014.05.013_bib15 article-title: A high-efficiency digital image correlation method based on a fast recursive scheme publication-title: Meas Sci Technol doi: 10.1088/0957-0233/21/3/035101 – volume: 56 start-page: 221 year: 2004 ident: 10.1016/j.optlaseng.2014.05.013_bib20 article-title: Lucas-Kanade 20 years on: a unifying framework publication-title: Int J Comput Vis doi: 10.1023/B:VISI.0000011205.11775.fd – volume: 53 start-page: 1277 year: 2013 ident: 10.1016/j.optlaseng.2014.05.013_bib21 article-title: Fast, robust and accurate digital image correlation calculation without redundant computations publication-title: Exp Mech doi: 10.1007/s11340-013-9717-6 – volume: 29 start-page: 261 year: 1989 ident: 10.1016/j.optlaseng.2014.05.013_bib17 article-title: Digital image correlation using Newton–Raphson method of partial differential correction publication-title: Exp Mech doi: 10.1007/BF02321405 – volume: 25 start-page: 232 year: 1985 ident: 10.1016/j.optlaseng.2014.05.013_bib2 article-title: Applications of digital-image-correlation techniques to experimental mechanics publication-title: Exp Mech doi: 10.1007/BF02325092
SSID	ssj0016411
Score	2.5222635
Snippet	The computational efficiency and measurement accuracy of the digital image correlation (DIC) have become more and more important in recent years. For the...
SourceID	proquest crossref elsevier
SourceType	Aggregation Database Enrichment Source Index Database Publisher
StartPage	73
SubjectTerms	Accuracy Algorithms Correlation analysis Deformation Digital Digital image correlation Inverse compositional Gauss–Newton algorithm Second-order shape function Shape functions Three dimensional Three-dimensional measurement
Title	High-efficiency and high-accuracy digital image correlation for three-dimensional measurement
URI	https://dx.doi.org/10.1016/j.optlaseng.2014.05.013 https://www.proquest.com/docview/1651440578
Volume	65
WOSCitedRecordID	wos000345492500010&url=https%3A%2F%2Fcvtisr.summon.serialssolutions.com%2F%23%21%2Fsearch%3Fho%3Df%26include.ft.matches%3Dt%26l%3Dnull%26q%3D
hasFullText	1
inHoldings	1
isFullTextHit
isPrint
journalDatabaseRights	– providerCode: PRVESC databaseName: Elsevier SD Freedom Collection Journals 2021 customDbUrl: eissn: 1873-0302 dateEnd: 99991231 omitProxy: false ssIdentifier: ssj0016411 issn: 0143-8166 databaseCode: AIEXJ dateStart: 19950101 isFulltext: true titleUrlDefault: https://www.sciencedirect.com providerName: Elsevier
link	http://cvtisr.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwtV3da9RAEF-0VdAH0apYv4ggvpSVXJLdbHwr5YrKcRW8SnyQZb_SXmmT8-4i_fOdyXdrpfXBl3Asu7m7nV9mJjOzvyHkbQJaX5gwpErrkEZG-VQDDKj1meYsyQJdsfN_m8TTqUjT5EuTillV7QTiPBfn58niv4oaxkDYeHT2H8Td3RQG4DMIHa4gdrjeSPBYuUFdxQxRHavEyDiSElNlTLnE7u52foStQnbmZ1iwY7A_x-mw5nDpHLXI-l8zduyc9XHEoS97sOgonsEFx4PASD_S8xt2pT2qCsd-LzsM7R27WsXMXD_ta1nNKvqRtBpJ56o4VvNheGLE2ormQcQypJicHKpczgY6s25l0lpf_0q9XocYTt4XizX-o_wIi_KimnM17E1Zm76fHsj9w8lEzsbp7N3iJ8UmY5iMbzqu3CabQcwS0OObu5_G6ecu7cSjUd3AsvnNFwoCr_zuv7kzlwx75a3MHpIHzWuGt1vD4xG55fItcn9APrlF7lbFv2b1mPy4BBkPROpdgIzXQMarIOMNIOMBZLw_IOMNIPOEHO6PZ3sfadN2g5pIRGvKmQkYGElfCRNkETzKKo4Tm0XM8thqLqxOrI6siMD50RgwUMJy3wU8MzpmKnxKNvIid8-I58OtRBxYlsFra-BEwsQo5I47o5wf6nCb8Hb3pGk46bE1yqlsiw9PZLftErdd-kzCtm8Tv1u4qGlZrl_yoRWPbLzL2muUALLrF79pBSpB_2JSTeWuKFdyxBnWR4Dhe36DOS_Ivf4heUk21svSvSJ3zK_1fLV83cDxN0hWrG4
linkProvider	Elsevier
openUrl	ctx_ver=Z39.88-2004&ctx_enc=info%3Aofi%2Fenc%3AUTF-8&rfr_id=info%3Asid%2Fsummon.serialssolutions.com&rft_val_fmt=info%3Aofi%2Ffmt%3Akev%3Amtx%3Ajournal&rft.genre=article&rft.atitle=High-efficiency+and+high-accuracy+digital+image+correlation+for+three-dimensional+measurement&rft.jtitle=Optics+and+lasers+in+engineering&rft.au=Gao%2C+Yue&rft.au=Cheng%2C+Teng&rft.au=Su%2C+Yong&rft.au=Xu%2C+Xiaohai&rft.date=2015-02-01&rft.issn=0143-8166&rft.volume=65&rft.spage=73&rft.epage=80&rft_id=info:doi/10.1016%2Fj.optlaseng.2014.05.013&rft.externalDBID=NO_FULL_TEXT
thumbnail_l	http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/lc.gif&issn=0143-8166&client=summon
thumbnail_m	http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/mc.gif&issn=0143-8166&client=summon
thumbnail_s	http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/sc.gif&issn=0143-8166&client=summon