Intuitionistic fuzzy information-driven total Bregman divergence fuzzy clustering with multiple local information constraints for image segmentation

Aiming at the shortcoming of existing robust intuitionistic fuzzy clustering and its variant algorithms in the presence of high noise, we will explore a novel intuitionistic fuzzy clustering-related segmentation algorithm with strong robustness. To enhance the anti-noise robustness and segmentation...

Celý popis

Uloženo v:

Podrobná bibliografie
Vydáno v:	The Visual computer Ročník 39; číslo 1; s. 149 - 181
Hlavní autoři:	Wu, Chengmao, Huang, Congcong, Zhang, Jiajia
Médium:	Journal Article
Jazyk:	angličtina
Vydáno:	Berlin/Heidelberg Springer Berlin Heidelberg 01.01.2023 Springer Nature B.V
Témata:	Algorithms Artificial Intelligence Clustering Computer Graphics Computer Science Divergence Euclidean geometry Fuzzy sets Genetic algorithms Image Processing and Computer Vision Image segmentation Neighborhoods Noise reduction Noise sensitivity Original Article Pixels Robustness (mathematics) Set theory Spatial data Statistical analysis Vision systems Image segmentation Local similarity measure Intuitionistic fuzzy clustering Intuitionistic fuzzy weighted local information factor Total Bregman divergence
ISSN:	0178-2789, 1432-2315
On-line přístup:	Získat plný text
Tagy:	Přidat tag Žádné tagy, Buďte první, kdo vytvoří štítek k tomuto záznamu!

Abstract	Aiming at the shortcoming of existing robust intuitionistic fuzzy clustering and its variant algorithms in the presence of high noise, we will explore a novel intuitionistic fuzzy clustering-related segmentation algorithm with strong robustness. To enhance the anti-noise robustness and segmentation accuracy of intuitionistic fuzzy clustering-related algorithms, an intuitionistic fuzzy information-driven total Bregman divergence fuzzy clustering with multiple local information constraints is proposed in this paper. In this algorithm, a modified total Bregman divergence with spatial information constraints is firstly constructed to replace existing squared Euclidean distance in intuitionistic fuzzy clustering, which can further enhance the ability of noise suppression. By introducing an intuitionistic fuzzy weighted local information into the objective function of intuitionistic fuzzy c-means clustering, its noise sensitivity can be reduced and image details can be preserved effectively. Combining neighborhood spatial information, neighborhood gray information with the normalized variance of neighborhood pixels, a local similarity measure between the current pixel and its neighborhood pixels is constructed to better describe the influence degree of neighborhood pixels on the current pixel, and it is adaptively embedded into modified total Bregman divergence-based intuitionistic fuzzy clustering. In the end, a robust total Bregman divergence-based fuzzy weighted local information clustering algorithm motivated by intuitionistic fuzzy information of the image is obtained to solve the problem of robust image segmentation, and its convergence is strictly proved by the Zangwill theorem. Many experimental results show that the segmentation accuracy ACC of the proposed algorithm can be as high as more than 90%, and the misclassification rate ME can be as low as less than 28%. Therefore, the proposed algorithm has better segmentation performance and robustness than the existing state-of-the-art intuitionistic fuzzy clustering-related segmentation algorithm in the presence of noise.
AbstractList	Aiming at the shortcoming of existing robust intuitionistic fuzzy clustering and its variant algorithms in the presence of high noise, we will explore a novel intuitionistic fuzzy clustering-related segmentation algorithm with strong robustness. To enhance the anti-noise robustness and segmentation accuracy of intuitionistic fuzzy clustering-related algorithms, an intuitionistic fuzzy information-driven total Bregman divergence fuzzy clustering with multiple local information constraints is proposed in this paper. In this algorithm, a modified total Bregman divergence with spatial information constraints is firstly constructed to replace existing squared Euclidean distance in intuitionistic fuzzy clustering, which can further enhance the ability of noise suppression. By introducing an intuitionistic fuzzy weighted local information into the objective function of intuitionistic fuzzy c-means clustering, its noise sensitivity can be reduced and image details can be preserved effectively. Combining neighborhood spatial information, neighborhood gray information with the normalized variance of neighborhood pixels, a local similarity measure between the current pixel and its neighborhood pixels is constructed to better describe the influence degree of neighborhood pixels on the current pixel, and it is adaptively embedded into modified total Bregman divergence-based intuitionistic fuzzy clustering. In the end, a robust total Bregman divergence-based fuzzy weighted local information clustering algorithm motivated by intuitionistic fuzzy information of the image is obtained to solve the problem of robust image segmentation, and its convergence is strictly proved by the Zangwill theorem. Many experimental results show that the segmentation accuracy ACC of the proposed algorithm can be as high as more than 90%, and the misclassification rate ME can be as low as less than 28%. Therefore, the proposed algorithm has better segmentation performance and robustness than the existing state-of-the-art intuitionistic fuzzy clustering-related segmentation algorithm in the presence of noise.
Author	Zhang, Jiajia Wu, Chengmao Huang, Congcong
Author_xml	– sequence: 1 givenname: Chengmao orcidid: 0000-0002-5881-4723 surname: Wu fullname: Wu, Chengmao organization: School of Electronic Engineering, Xi’an University of Posts and Telecommunications – sequence: 2 givenname: Congcong orcidid: 0000-0002-2971-8978 surname: Huang fullname: Huang, Congcong email: huangcongcong_1234@163.com organization: School of Electronic Engineering, Xi’an University of Posts and Telecommunications – sequence: 3 givenname: Jiajia orcidid: 0000-0002-3144-4179 surname: Zhang fullname: Zhang, Jiajia organization: School of Electronic Engineering, Xi’an University of Posts and Telecommunications
BookMark	eNp9kE1OwzAQhS1UJErhAqwssQ7YcRo7S6j4qVSJDawt13GCq8QOtgNqz8GBcZpKIBZdWNY8zTcz752DibFGAXCF0Q1GiN56hAjFCUqHR3CRsBMwxRlJk1jNJ2CKMGVJSllxBs6936BY06yYgu-lCb0O2hrtg5aw6ne7LdSmsq4Vg5yUTn8qA4MNooH3TtWtMLCMmquVkepAyKb3QTltavilwzts-yborlGwsTJyfwZCaY0PTmgTPIwq1K2oFfRxsDJh33IBTivReHV5-Gfg7fHhdfGcrF6elou7VSKjxZDILMsJy9YVzQVLGZWFwlQQtqZ5NCrmWVXkEolK0HIuCaoULkqxZqikOGOZRGQGrse5nbMfvfKBb2zvTFzJ0yIGVqQ5w7ErHbuks947VfHOxZvdlmPEh_T5mD6P6fN9-pxFiP2DpB7NDdab4ygZUd8NeSr3e9UR6gc_3aCK
CitedBy_id	crossref_primary_10_1007_s00371_022_02464_8 crossref_primary_10_32604_cmes_2023_025499 crossref_primary_10_1007_s00034_022_02175_4 crossref_primary_10_1016_j_asoc_2023_110460 crossref_primary_10_1016_j_compbiomed_2025_110458 crossref_primary_10_1038_s41598_023_47089_6
Cites_doi	10.1007/s41870-017-0039-2 10.3969/j.issn.1004-4132.2010.04.009 10.1109/91.227387 10.1007/s11042-018-5954-0 10.1016/j.asoc.2010.05.005 10.1016/S0019-9958(65)90241-X 10.1016/S0165-0114(86)80034-3 10.5772/intechopen.74514 10.1007/s40815-020-00824-x 10.1137/1.9781611972740.22 10.1504/IJBIDM.2008.017975 10.3969/j.issn.1000-1093.2019.09.014(inChinese) 10.1007/s00138-014-0606-5 10.1109/PROC.1979.11327 10.14311/CEJ.2018.04.0041 10.1016/j.dsp.2013.07.005 10.1109/tip.2011.2146190 10.1109/tpami.1980.4766964 10.1109/TFUZZ.2020.2973121 10.3390/e20040256 10.1109/TMI.2010.2086464 10.1109/42.996338 10.1080/01969727308546047 10.1007/978-3-319-49568-2_52 10.3233/JIFS-192005 10.1016/j.compag.2021.106237 10.1016/j.rcim.2019.03.001 10.3233/JIFS-169809 10.1007/s11222-015-9576-3 10.1109/TSMCB.2004.831165 10.1016/j.neucom.2021.04.094 10.1016/j.jneumeth.2010.03.004 10.1016/j.patcog.2006.07.011 10.1007/s00500-019-04169-y 10.1109/tpami.2012.44 10.1109/TIP.2012.2219547 10.1016/j.dsp.2019.102615 10.3389/fpls.2020.00510 10.1016/j.neucom.2018.05.116 10.1016/j.patcog.2011.02.009 10.3969/j.issn.1001-3695.2014.09.073(inChinese) 10.1016/j.patrec.2013.04.021 10.4108/eai.13-7-2018.159622 10.1109/TFUZZ.2018.2852289 10.1016/j.eswa.2014.01.003 10.1016/j.dsp.2018.01.008 10.1109/LSP.2013.2244080 10.1007/s10462-010-9155-0 10.1016/0041-5553(67)90040-7 10.1109/34.589206 10.1016/j.asoc.2015.12.022 10.1080/18756891.2013.865830 10.1080/03081077908547452 10.1109/TFUZZ.2013.2280141 10.1016/S0019-9958(80)90156-4 10.1109/JBHI.2018.2884208 10.1016/j.measurement.2021.109477 10.1142/S0218213015500165 10.1109/TIP.2010.2040763 10.1016/S1361-8415(00)00041-4 10.1016/j.asoc.2020.106468 10.1109/34.868688 10.1007/978-1-4757-0450-1 10.1049/iet-ipr.2018.5597 10.1007/s00500-014-1264-2 10.1007/s00034-012-9531-x 10.1016/S0165-0114(98)00244-9 10.1109/CIMCA.2005.1631233 10.1109/TBDATA.2016.2622288 10.1109/SMC.2016.7844622 10.1109/ICCV.2001.937655 10.1109/IEMBS.2003.1279866 10.1109/CCIP.2016.7802852 10.1109/ICComm.2016.7528317
ContentType	Journal Article
Copyright	The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature 2021 The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature 2021.
Copyright_xml	– notice: The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature 2021 – notice: The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature 2021.
DBID	AAYXX CITATION 8FE 8FG AFKRA ARAPS AZQEC BENPR BGLVJ CCPQU DWQXO GNUQQ HCIFZ JQ2 K7- P5Z P62 PHGZM PHGZT PKEHL PQEST PQGLB PQQKQ PQUKI
DOI	10.1007/s00371-021-02319-8
DatabaseName	CrossRef ProQuest SciTech Collection ProQuest Technology Collection ProQuest Central UK/Ireland Advanced Technologies & Computer Science Collection ProQuest Central Essentials ProQuest Central Technology collection ProQuest One ProQuest Central ProQuest Central Student SciTech Premium Collection ProQuest Computer Science Collection Computer Science Database ProQuest advanced technologies & aerospace journals ProQuest Advanced Technologies & Aerospace Collection ProQuest Databases ProQuest One Academic (New) ProQuest One Academic Middle East (New) ProQuest One Academic Eastern Edition (DO NOT USE) One Applied & Life Sciences ProQuest One Academic (retired) ProQuest One Academic UKI Edition
DatabaseTitle	CrossRef Advanced Technologies & Aerospace Collection Computer Science Database ProQuest Central Student Technology Collection ProQuest One Academic Middle East (New) ProQuest Advanced Technologies & Aerospace Collection ProQuest Central Essentials ProQuest Computer Science Collection ProQuest One Academic Eastern Edition SciTech Premium Collection ProQuest One Community College ProQuest Technology Collection ProQuest SciTech Collection ProQuest Central Advanced Technologies & Aerospace Database ProQuest One Applied & Life Sciences ProQuest One Academic UKI Edition ProQuest Central Korea ProQuest Central (New) ProQuest One Academic ProQuest One Academic (New)
DatabaseTitleList	Advanced Technologies & Aerospace Collection
Database_xml	– sequence: 1 dbid: P5Z name: Advanced Technologies & Aerospace Database url: https://search.proquest.com/hightechjournals sourceTypes: Aggregation Database
DeliveryMethod	fulltext_linktorsrc
Discipline	Engineering Computer Science
EISSN	1432-2315
EndPage	181
ExternalDocumentID	10_1007_s00371_021_02319_8
GrantInformation_xml	– fundername: National Natural Science Foundation of China grantid: 61671377; 51709228 funderid: http://dx.doi.org/10.13039/501100001809 – fundername: Shaanxi Natural Science Foundation of China grantid: 2016JM8034; 2017JM6107; 2018JM4018
GroupedDBID	-4Z -59 -5G -BR -EM -Y2 -~C -~X .86 .DC .VR 06D 0R~ 0VY 123 1N0 1SB 2.D 203 28- 29R 2J2 2JN 2JY 2KG 2KM 2LR 2P1 2VQ 2~H 30V 4.4 406 408 409 40D 40E 5QI 5VS 67Z 6NX 6TJ 78A 8TC 8UJ 95- 95. 95~ 96X AAAVM AABHQ AACDK AAHNG AAIAL AAJBT AAJKR AANZL AAOBN AARHV AARTL AASML AATNV AATVU AAUYE AAWCG AAYIU AAYOK AAYQN AAYTO AAYZH ABAKF ABBBX ABBXA ABDPE ABDZT ABECU ABFTV ABHLI ABHQN ABJNI ABJOX ABKCH ABKTR ABMNI ABMQK ABNWP ABQBU ABQSL ABSXP ABTEG ABTHY ABTKH ABTMW ABULA ABWNU ABXPI ACAOD ACBXY ACDTI ACGFS ACHSB ACHXU ACKNC ACMDZ ACMLO ACOKC ACOMO ACPIV ACZOJ ADHHG ADHIR ADIMF ADINQ ADKNI ADKPE ADQRH ADRFC ADTPH ADURQ ADYFF ADZKW AEBTG AEFIE AEFQL AEGAL AEGNC AEJHL AEJRE AEKMD AEMSY AENEX AEOHA AEPYU AESKC AETLH AEVLU AEXYK AFBBN AFEXP AFFNX AFGCZ AFKRA AFLOW AFQWF AFWTZ AFZKB AGAYW AGDGC AGGDS AGJBK AGMZJ AGQEE AGQMX AGRTI AGWIL AGWZB AGYKE AHAVH AHBYD AHSBF AHYZX AIAKS AIGIU AIIXL AILAN AITGF AJBLW AJRNO AJZVZ ALMA_UNASSIGNED_HOLDINGS ALWAN AMKLP AMXSW AMYLF AMYQR AOCGG ARAPS ARMRJ ASPBG AVWKF AXYYD AYJHY AZFZN B-. BA0 BBWZM BDATZ BENPR BGLVJ BGNMA BSONS CAG CCPQU COF CS3 CSCUP DDRTE DL5 DNIVK DPUIP DU5 EBLON EBS EIOEI EJD ESBYG FEDTE FERAY FFXSO FIGPU FINBP FNLPD FRRFC FSGXE FWDCC GGCAI GGRSB GJIRD GNWQR GQ6 GQ7 GQ8 GXS H13 HCIFZ HF~ HG5 HG6 HMJXF HQYDN HRMNR HVGLF HZ~ I09 IHE IJ- IKXTQ ITM IWAJR IXC IZIGR IZQ I~X I~Z J-C J0Z JBSCW JCJTX JZLTJ K7- KDC KOV KOW LAS LLZTM M4Y MA- N2Q N9A NB0 NDZJH NPVJJ NQJWS NU0 O9- O93 O9G O9I O9J OAM P19 P2P P9O PF0 PT4 PT5 QOK QOS R4E R89 R9I RHV RIG RNI RNS ROL RPX RSV RZK S16 S1Z S26 S27 S28 S3B SAP SCJ SCLPG SCO SDH SDM SHX SISQX SJYHP SNE SNPRN SNX SOHCF SOJ SPISZ SRMVM SSLCW STPWE SZN T13 T16 TN5 TSG TSK TSV TUC U2A UG4 UOJIU UTJUX UZXMN VC2 VFIZW W23 W48 WK8 YLTOR YOT Z45 Z5O Z7R Z7S Z7X Z7Z Z83 Z86 Z88 Z8M Z8N Z8R Z8T Z8W Z92 ZMTXR ~EX AAPKM AAYXX ABBRH ABDBE ABFSG ABRTQ ACSTC ADHKG ADKFA AEZWR AFDZB AFFHD AFHIU AFOHR AGQPQ AHPBZ AHWEU AIXLP ATHPR AYFIA CITATION PHGZM PHGZT PQGLB 8FE 8FG AZQEC DWQXO GNUQQ JQ2 P62 PKEHL PQEST PQQKQ PQUKI
ID	FETCH-LOGICAL-c319t-c446384bf76a8287c9e17a38b76789a54f96c0afa7d5c30fe19dab80d71484c03
IEDL.DBID	RSV
ISICitedReferencesCount	5
ISICitedReferencesURI	http://www.webofscience.com/api/gateway?GWVersion=2&SrcApp=Summon&SrcAuth=ProQuest&DestLinkType=CitingArticles&DestApp=WOS_CPL&KeyUT=000717889400001&url=https%3A%2F%2Fcvtisr.summon.serialssolutions.com%2F%23%21%2Fsearch%3Fho%3Df%26include.ft.matches%3Dt%26l%3Dnull%26q%3D
ISSN	0178-2789
IngestDate	Wed Nov 05 02:09:45 EST 2025 Sat Nov 29 02:23:28 EST 2025 Tue Nov 18 21:27:00 EST 2025 Fri Feb 21 02:46:17 EST 2025
IsPeerReviewed	true
IsScholarly	true
Issue	1
Keywords	Image segmentation Local similarity measure Intuitionistic fuzzy clustering Intuitionistic fuzzy weighted local information factor Total Bregman divergence
Language	English
LinkModel	DirectLink
MergedId	FETCHMERGED-LOGICAL-c319t-c446384bf76a8287c9e17a38b76789a54f96c0afa7d5c30fe19dab80d71484c03
Notes	ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 14
ORCID	0000-0002-2971-8978 0000-0002-3144-4179 0000-0002-5881-4723
PQID	2917892681
PQPubID	2043737
PageCount	33
ParticipantIDs	proquest_journals_2917892681 crossref_primary_10_1007_s00371_021_02319_8 crossref_citationtrail_10_1007_s00371_021_02319_8 springer_journals_10_1007_s00371_021_02319_8
PublicationCentury	2000
PublicationDate	2023-01-01
PublicationDateYYYYMMDD	2023-01-01
PublicationDate_xml	– month: 01 year: 2023 text: 2023-01-01 day: 01
PublicationDecade	2020
PublicationPlace	Berlin/Heidelberg
PublicationPlace_xml	– name: Berlin/Heidelberg – name: Heidelberg
PublicationSubtitle	International Journal of Computer Graphics
PublicationTitle	The Visual computer
PublicationTitleAbbrev	Vis Comput
PublicationYear	2023
Publisher	Springer Berlin Heidelberg Springer Nature B.V
Publisher_xml	– name: Springer Berlin Heidelberg – name: Springer Nature B.V
References	Benaichouche, Oulhadj, Siarry (CR17) 2013; 23 Alipour, Shanbehzadeh (CR12) 2014; 25 Liu (CR54) 2011 Ahmed, Yamany, Mohamed (CR24) 2002; 21 Giordana, Pieczynski (CR73) 1997; 19 Wu, Yang (CR61) 2020; 97 Liu, Vemuri, Amari (CR55) 2012; 34 CR76 Zangwill (CR71) 1969 Tang, Chen, Wang (CR3) 2020; 11 Atanassov (CR29) 1986; 20 Pelekis, Iakovidis, Kotsifakos (CR28) 2008; 3 Chen, Zhang (CR25) 2004; 34 Bezdek (CR77) 1974; 3 Luo, Wang, Wang (CR10) 2016; 541 Kaur, Soni, Gosain (CR43) 2012; 11 Gong, Liang, Shi (CR70) 2013; 22 Kaur (CR37) 2017; 9 Wu, Zhang (CR69) 2020; 94 CR9 Verma, Agrawal (CR35) 2015; 24 Yager (CR32) 1980; 44 Cai, Chen, Zhang (CR27) 2007; 40 Wang, Chen, Pan (CR14) 2010; 188 Zhao, Zeng, Liu (CR42) 2020; 28 Xu, Wu (CR34) 2010; 21 Chen, Li, Wang (CR48) 2019; 13 CR80 Qiu, Xiao, Yu (CR21) 2013; 34 Verma, Agrawal, Sharan (CR47) 2015; 46 Wu, Sun (CR57) 2019; 40 Hua, Cheng, Wang (CR58) 2018; 75 Olabarriaga, Smeulders (CR20) 2001; 5 Bezdek (CR23) 1981 Kumar, Verma, Mehra (CR38) 2018; 78 Dante, Kinani, Rubio (CR53) 2020; 22 Bezdek (CR72) 1980; 2 Dante (CR40) 2020; 39 Kumar (CR78) 2019; 78 Tang, Lin, Wang (CR4) 2019; 59 Zhao, Liu, Fan (CR51) 2018; 312 Guo, Sengur (CR74) 2010; 32 Krinidis, Chatzis (CR19) 2010; 19 Balafar, Ramli, Saripan (CR16) 2010; 33 Hasnat, Alata, Tremeau (CR66) 2016; 26 CR15 Krishnapuram, Keller (CR36) 1993; 1 CR11 Huang, Lin, Wu (CR18) 2015; 19 Chaira (CR30) 2011; 11 Kumar, Agrawal, Verma (CR41) 2020; 24 Szmidt, Kacprzyk (CR64) 2000; 114 Chaira, Panwar (CR33) 2014; 7 Arora, Tushir (CR49) 2018; 35 Tsai, Lin (CR44) 2011; 44 Banerjee, Merugu, Dhillon (CR65) 2005; 6 Shi, Malik (CR2) 2000; 22 Yager (CR31) 1979; 5 Groen (CR68) 1996; 14 Despotović, Ansteenkiste, Philips (CR60) 2013; 20 Isidoro, Martins, Carvalho (CR6) 2021; 180 Gharib (CR75) 2018 Wang, Fan, Lou (CR45) 2014; 31 Zhao, Fan, Liu (CR50) 2018; 27 Fuchs, Kröger, Garbe (CR5) 2021; 453 Zhao, Fan, Liu (CR79) 2014; 41 Bregman (CR67) 1967; 7 Vemuri, Liu, Amari (CR56) 2011; 30 Zhang, Qin (CR8) 2018; 27 CR26 Li, Huang, Ding (CR13) 2011; 20 Chen, Tang, Zhou (CR7) 2021; 187 Bai, Zhang, Liu (CR52) 2019; 23 Coleman, Andrews (CR22) 1979; 67 CR63 Zadeh (CR62) 1965; 8 Arora, Tushir (CR39) 2019; 7 Hua, Fan, Cheng (CR59) 2018; 20 Lin (CR46) 2014; 22 Shivhare, Gupta (CR1) 2015; 4 KP Lin (2319_CR46) 2014; 22 LA Zadeh (2319_CR62) 1965; 8 W Cai (2319_CR27) 2007; 40 2319_CR76 J Arora (2319_CR49) 2018; 35 GB Coleman (2319_CR22) 1979; 67 T Chaira (2319_CR33) 2014; 7 E Szmidt (2319_CR64) 2000; 114 D Kumar (2319_CR78) 2019; 78 2319_CR80 S Chen (2319_CR25) 2004; 34 P Fuchs (2319_CR5) 2021; 453 C Wu (2319_CR61) 2020; 97 WI Zangwill (2319_CR71) 1969 H Verma (2319_CR47) 2015; 46 N Pelekis (2319_CR28) 2008; 3 X Chen (2319_CR48) 2019; 13 2319_CR26 J Shi (2319_CR2) 2000; 22 Z Wang (2319_CR45) 2014; 31 RR Gharib (2319_CR75) 2018 M Liu (2319_CR55) 2012; 34 M Gong (2319_CR70) 2013; 22 2319_CR63 T Chaira (2319_CR30) 2011; 11 P Kaur (2319_CR43) 2012; 11 J Arora (2319_CR39) 2019; 7 I Despotović (2319_CR60) 2013; 20 PD Groen (2319_CR68) 1996; 14 C Wu (2319_CR69) 2020; 94 LM Bregman (2319_CR67) 1967; 7 C Li (2319_CR13) 2011; 20 X Hua (2319_CR58) 2018; 75 C Qiu (2319_CR21) 2013; 34 S Alipour (2319_CR12) 2014; 25 H Verma (2319_CR35) 2015; 24 X Hua (2319_CR59) 2018; 20 A Banerjee (2319_CR65) 2005; 6 J Luo (2319_CR10) 2016; 541 2319_CR15 QZ Zhang (2319_CR8) 2018; 27 MA Balafar (2319_CR16) 2010; 33 CW Huang (2319_CR18) 2015; 19 KT Atanassov (2319_CR29) 1986; 20 X Bai (2319_CR52) 2019; 23 D Kumar (2319_CR38) 2018; 78 F Zhao (2319_CR79) 2014; 41 2319_CR11 RR Yager (2319_CR32) 1980; 44 2319_CR9 RR Yager (2319_CR31) 1979; 5 MV Dante (2319_CR40) 2020; 39 Y Guo (2319_CR74) 2010; 32 M Liu (2319_CR54) 2011 R Krishnapuram (2319_CR36) 1993; 1 P Kaur (2319_CR37) 2017; 9 S Krinidis (2319_CR19) 2010; 19 MN Ahmed (2319_CR24) 2002; 21 F Zhao (2319_CR50) 2018; 27 N Giordana (2319_CR73) 1997; 19 MY Chen (2319_CR7) 2021; 187 JC Bezdek (2319_CR23) 1981 YC Tang (2319_CR3) 2020; 11 P Shivhare (2319_CR1) 2015; 4 MA Hasnat (2319_CR66) 2016; 26 Z Xu (2319_CR34) 2010; 21 DM Tsai (2319_CR44) 2011; 44 D Kumar (2319_CR41) 2020; 24 SD Olabarriaga (2319_CR20) 2001; 5 F Zhao (2319_CR42) 2020; 28 JC Bezdek (2319_CR77) 1974; 3 F Zhao (2319_CR51) 2018; 312 JMGP Isidoro (2319_CR6) 2021; 180 MV Dante (2319_CR53) 2020; 22 JC Bezdek (2319_CR72) 1980; 2 BC Vemuri (2319_CR56) 2011; 30 C Wu (2319_CR57) 2019; 40 YC Tang (2319_CR4) 2019; 59 L Wang (2319_CR14) 2010; 188 AN Benaichouche (2319_CR17) 2013; 23
References_xml	– volume: 9 start-page: 345 issue: 4 year: 2017 end-page: 351 ident: CR37 article-title: Intuitionistic fuzzy sets based credibilistic fuzzy C-means clustering for medical image segmentation publication-title: Int. J. Inf. Technol. doi: 10.1007/s41870-017-0039-2 – volume: 21 start-page: 580 issue: 4 year: 2010 end-page: 590 ident: CR34 article-title: Intuitionistic fuzzy c-means clustering algorithms J publication-title: . Syst. Eng. Electron. doi: 10.3969/j.issn.1004-4132.2010.04.009 – volume: 1 start-page: 98 issue: 2 year: 1993 end-page: 110 ident: CR36 article-title: A possibilistic approach to clustering publication-title: IEEE Trans. Fuzzy Syst. doi: 10.1109/91.227387 – volume: 78 start-page: 12663 issue: 6 year: 2019 end-page: 12687 ident: CR78 article-title: A modified intuitionistic fuzzy c-means clustering approach to segment human brain MRI image publication-title: Multimed. Tools and Appl. doi: 10.1007/s11042-018-5954-0 – volume: 11 start-page: 1711 issue: 2 year: 2011 end-page: 1717 ident: CR30 article-title: A novel intuitionistic fuzzy c means clustering algorithm and its application to medical images publication-title: Appl. Soft Comput. doi: 10.1016/j.asoc.2010.05.005 – volume: 8 start-page: 338 issue: 3 year: 1965 end-page: 353 ident: CR62 article-title: Fuzzy sets publication-title: Inf. Control doi: 10.1016/S0019-9958(65)90241-X – volume: 20 start-page: 87 issue: 1 year: 1986 end-page: 96 ident: CR29 article-title: Intuitionistic fuzzy sets publication-title: Fuzzy Sets Syst. doi: 10.1016/S0165-0114(86)80034-3 – year: 2018 ident: CR75 article-title: Incorporating local data and KL membership divergence into hard c-means clustering for fuzzy and noise-robust data segmentation publication-title: Mach. Learn. Data Min. doi: 10.5772/intechopen.74514 – volume: 22 start-page: 901 issue: 3 year: 2020 end-page: 916 ident: CR53 article-title: Color-based image segmentation by means of a robust intuitionistic fuzzy c-means algorithm publication-title: Int. J. Fuzzy Syst. doi: 10.1007/s40815-020-00824-x – volume: 6 start-page: 1705 issue: 4 year: 2005 end-page: 1749 ident: CR65 article-title: Clustering with Bregman divergences publication-title: J. Mach. Learn. Res. doi: 10.1137/1.9781611972740.22 – volume: 3 start-page: 45 issue: 1 year: 2008 end-page: 65 ident: CR28 article-title: Fuzzy clustering of intuitionistic fuzzy data publication-title: Int. J. Bus. Intell. Data Min. doi: 10.1504/IJBIDM.2008.017975 – volume: 40 start-page: 1890 issue: 09 year: 2019 end-page: 1901 ident: CR57 article-title: Adaptive robust graph fuzzy clustering algorithm based on total divergence publication-title: Acta Armamentarii doi: 10.3969/j.issn.1000-1093.2019.09.014(inChinese) – volume: 14 start-page: 237 issue: 4 year: 1996 end-page: 253 ident: CR68 article-title: An introduction to total least squares publication-title: Nieuw Archief voor Wiskunde – volume: 25 start-page: 1469 issue: 6 year: 2014 end-page: 1488 ident: CR12 article-title: Fast automatic medical image segmentation based on spatial kernel fuzzy c-means on level set method publication-title: Mach. Vis. Appl. doi: 10.1007/s00138-014-0606-5 – volume: 67 start-page: 773 issue: 5 year: 1979 end-page: 785 ident: CR22 article-title: Image segmentation by clustering publication-title: P. IEEE doi: 10.1109/PROC.1979.11327 – volume: 27 start-page: 513 issue: 4 year: 2018 end-page: 524 ident: CR8 article-title: Application of machine vision technology in road detection publication-title: Civ. Eng. J. doi: 10.14311/CEJ.2018.04.0041 – volume: 23 start-page: 1390 issue: 5 year: 2013 end-page: 1400 ident: CR17 article-title: Improved spatial fuzzy c-means clustering for image segmentation using PSO initialization, Mahalanobis distance and post-segmentation correction publication-title: Digit. Signal Process. doi: 10.1016/j.dsp.2013.07.005 – ident: CR80 – volume: 20 start-page: 2007 issue: 7 year: 2011 end-page: 2016 ident: CR13 article-title: A level set method for image segmentation in the presence of intensity inhomogeneities with application to MRI publication-title: IEEE Trans. Image Process. doi: 10.1109/tip.2011.2146190 – volume: 2 start-page: 1 issue: 1 year: 1980 end-page: 8 ident: CR72 article-title: A convergence theorem for the fuzzy ISODATA clustering algorithm publication-title: IEEE Trans. Pattern Anal. Mach. Intell. doi: 10.1109/tpami.1980.4766964 – volume: 28 start-page: 1023 issue: 6 year: 2020 end-page: 1034 ident: CR42 article-title: Semi-supervised approach to surrogate-assisted multi objective kernel intuitionistic fuzzy clustering algorithm for color image segmentation publication-title: IEEE Trans. Fuzzy Syst. doi: 10.1109/TFUZZ.2020.2973121 – volume: 20 start-page: 256 issue: 4 year: 2018 ident: CR59 article-title: Information geometry for radar target detection with total Jensen-Bregman divergence publication-title: Entropy doi: 10.3390/e20040256 – volume: 30 start-page: 475 issue: 2 year: 2011 end-page: 483 ident: CR56 article-title: Total Bregman divergence and its applications to DTI analysis publication-title: IEEE Trans. Med. Imaging doi: 10.1109/TMI.2010.2086464 – volume: 21 start-page: 193 issue: 3 year: 2002 end-page: 199 ident: CR24 article-title: A modified fuzzy c-means algorithm for bias field estimation and segmentation of MRI data publication-title: IEEE Trans. Med. Imaging doi: 10.1109/42.996338 – ident: CR15 – volume: 3 start-page: 58 issue: 3 year: 1974 end-page: 73 ident: CR77 article-title: Cluster validity with fuzzy sets publication-title: J. Cybern. doi: 10.1080/01969727308546047 – volume: 541 start-page: 365 year: 2016 end-page: 370 ident: CR10 article-title: Automatic image segmentation of grape based on computer vision publication-title: Recent Dev. Intell. Syst. Interact. Appl. doi: 10.1007/978-3-319-49568-2_52 – volume: 39 start-page: 1097 issue: 1 year: 2020 end-page: 1108 ident: CR40 article-title: Redescending intuitionistic fuzzy clustering to brain magnetic resonance image segmentation publication-title: J. Intell. Fuzzy Syst. doi: 10.3233/JIFS-192005 – volume: 187 year: 2021 ident: CR7 article-title: 3D global mapping of large-scale unstructured orchard integrating eye-in-hand stereo vision and SLAM publication-title: Comput. Electron. Agric. doi: 10.1016/j.compag.2021.106237 – ident: CR11 – ident: CR9 – volume: 59 start-page: 36 year: 2019 end-page: 46 ident: CR4 article-title: Real-time detection of surface deformation and strain in recycled aggregate concrete-filled steel tubular columns via four-ocular vision publication-title: Robot. Comput.-Integr. Manuf. doi: 10.1016/j.rcim.2019.03.001 – volume: 35 start-page: 5255 issue: 5 year: 2018 end-page: 5264 ident: CR49 article-title: Robust spatial intuitionistic fuzzy c-means with city-block distance clustering for image segmentation publication-title: J. Intell. Fuzzy Syst. doi: 10.3233/JIFS-169809 – volume: 26 start-page: 861 issue: 4 year: 2016 end-page: 880 ident: CR66 article-title: Model-based hierarchical clustering with Bregman divergences and Fishers mixture model: application to depth image analysis publication-title: Stats Comput. doi: 10.1007/s11222-015-9576-3 – volume: 11 start-page: 65 issue: 3 year: 2012 end-page: 76 ident: CR43 article-title: Novel intuitionistic fuzzy c-means clustering for linearly and nonlinearly separable data publication-title: WSEAS Trans. Comput. – volume: 34 start-page: 1907 issue: 4 year: 2004 end-page: 1916 ident: CR25 article-title: Robust image segmentation using FCM with spatial constraints based on new kernel-induced distance measure publication-title: IEEE Trans. Syst. Man Cybern. doi: 10.1109/TSMCB.2004.831165 – volume: 453 start-page: 85 year: 2021 end-page: 96 ident: CR5 article-title: Defect detection in CT scans of cast aluminum parts: a machine vision perspective publication-title: Neurocomputing doi: 10.1016/j.neucom.2021.04.094 – volume: 188 start-page: 316 issue: 2 year: 2010 end-page: 325 ident: CR14 article-title: Level set segmentation of brain magnetic resonance images based on local gaussian distribution fitting energy publication-title: J. Neurosci. Methods doi: 10.1016/j.jneumeth.2010.03.004 – ident: CR26 – volume: 40 start-page: 825 issue: 3 year: 2007 end-page: 838 ident: CR27 article-title: Fast and robust fuzzy c-means clustering algorithms incorporating local information for image segmentation publication-title: Pattern Recognit. doi: 10.1016/j.patcog.2006.07.011 – volume: 24 start-page: 4003 issue: 6 year: 2020 end-page: 4026 ident: CR41 article-title: Kernel intuitionistic fuzzy entropy clustering for MRI image segmentation publication-title: Soft Comput. doi: 10.1007/s00500-019-04169-y – volume: 34 start-page: 2407 issue: 12 year: 2012 end-page: 2419 ident: CR55 article-title: Shape retrieval using hierarchical total Bregman soft clustering publication-title: IEEE Trans. Pattern Anal. Mach. Intell. doi: 10.1109/tpami.2012.44 – volume: 22 start-page: 573 issue: 2 year: 2013 end-page: 584 ident: CR70 article-title: Fuzzy c-means clustering with local information and kernel metric for image segmentation publication-title: IEEE Trans. Image Process. doi: 10.1109/TIP.2012.2219547 – year: 2011 ident: CR54 publication-title: Total Bregman Divergence, a Robust Divergence Measure, and Its Applications – volume: 97 year: 2020 ident: CR61 article-title: Robust credibilistic fuzzy local information clustering with spatial information constraints publication-title: Digit. Signal Process. doi: 10.1016/j.dsp.2019.102615 – volume: 11 start-page: 1 year: 2020 end-page: 17 ident: CR3 article-title: Recognition and localization methods for vision-based fruit picking robots: a review publication-title: Front Plant Sci. doi: 10.3389/fpls.2020.00510 – volume: 312 start-page: 296 year: 2018 end-page: 309 ident: CR51 article-title: Intuitionistic fuzzy set approach to multi-objective evolutionary clustering with multiple spatial information for image segmentation publication-title: Neurocomputing doi: 10.1016/j.neucom.2018.05.116 – volume: 44 start-page: 1750 year: 2011 end-page: 1760 ident: CR44 article-title: Fuzzy c-means based clustering for linearly and nonlinearly separable data publication-title: Pattern Recognit. doi: 10.1016/j.patcog.2011.02.009 – volume: 31 start-page: 2864 issue: 9 year: 2014 end-page: 2872 ident: CR45 article-title: Intuitionistic fuzzy c-mean clustering algorithm incorporating local information for image segmentation publication-title: Appl. Res. Comput. doi: 10.3969/j.issn.1001-3695.2014.09.073(inChinese) – volume: 34 start-page: 1329 issue: 12 year: 2013 end-page: 1338 ident: CR21 article-title: A modified interval type-2 fuzzy c-means algorithm with application in MR image segmentation publication-title: Pattern Recognit. Lett. doi: 10.1016/j.patrec.2013.04.021 – volume: 7 issue: 24 year: 2019 ident: CR39 article-title: A new semi-supervised intuitionistic fuzzy c-means clustering publication-title: ICST Trans. Scalable Inf. Syst. doi: 10.4108/eai.13-7-2018.159622 – volume: 27 start-page: 387 issue: 2 year: 2018 end-page: 401 ident: CR50 article-title: Noise robust multi-objective evolutionary clustering image segmentation motivated by intuitionistic fuzzy information publication-title: IEEE T. Fuzzy Syst. doi: 10.1109/TFUZZ.2018.2852289 – volume: 41 start-page: 4083 issue: 9 year: 2014 end-page: 4093 ident: CR79 article-title: Optimal-selection-based suppressed fuzzy c-means clustering algorithm with self-tuning non-local spatial information for image segmentation publication-title: Expert Syst. Appl. doi: 10.1016/j.eswa.2014.01.003 – volume: 75 start-page: 232 issue: 75 year: 2018 end-page: 241 ident: CR58 article-title: Geometric target detection based on total Bregman divergence publication-title: Digit. Signal Process. doi: 10.1016/j.dsp.2018.01.008 – volume: 20 start-page: 295 issue: 4 year: 2013 end-page: 298 ident: CR60 article-title: Spatially coherent fuzzy clustering for accurate and noise-robust image segmentation publication-title: IEEE Signal Process. Lett. doi: 10.1109/LSP.2013.2244080 – volume: 4 start-page: 153 issue: 3 year: 2015 end-page: 157 ident: CR1 article-title: Review of image segmentation techniques including Pre & Post processing operations publication-title: Int. J. Eng. Adv. Technol. – volume: 33 start-page: 261 issue: 3 year: 2010 end-page: 274 ident: CR16 article-title: Review of brain MRI image segmentation methods publication-title: Artif. Intell. Rev. doi: 10.1007/s10462-010-9155-0 – volume: 7 start-page: 200 issue: 3 year: 1967 end-page: 217 ident: CR67 article-title: The relaxation method of finding the common points of convex sets and its application to the solution of problems in convex programming publication-title: USSR Comput. Math. Math. Phys. doi: 10.1016/0041-5553(67)90040-7 – volume: 19 start-page: 475 issue: 5 year: 1997 ident: CR73 article-title: Estimation of generalized multi-sensor hidden Markov chains and unsupervised image segmentation publication-title: IEEE Trans. Pattern Anal. Mach. Intell. doi: 10.1109/34.589206 – volume: 46 start-page: 543 issue: C year: 2015 end-page: 557 ident: CR47 article-title: An improved intuitionistic fuzzy c-means clustering algorithm incorporating local information for brain image segmentation publication-title: Appl. Soft Comput. doi: 10.1016/j.asoc.2015.12.022 – ident: CR63 – volume: 7 start-page: 360 issue: 2 year: 2014 end-page: 370 ident: CR33 article-title: An Atanassov’s intuitionistic fuzzy kernel clustering for medical image segmentation publication-title: Int. J. Comput. Int. Sys. doi: 10.1080/18756891.2013.865830 – volume: 5 start-page: 221 issue: 4 year: 1979 end-page: 229 ident: CR31 article-title: On the measure of fuzziness and negation Part I: membership in the unit interval publication-title: Int. J. Gen. Syst. doi: 10.1080/03081077908547452 – volume: 22 start-page: 1074 issue: 5 year: 2014 end-page: 1087 ident: CR46 article-title: A novel evolutionary kernel intuitionistic fuzzy c-means clustering algorithm publication-title: IEEE Trans. Fuzzy Syst. doi: 10.1109/TFUZZ.2013.2280141 – volume: 44 start-page: 236 issue: 3 year: 1980 end-page: 260 ident: CR32 article-title: On the measure of fuzziness and negation II. Lattices publication-title: Inf. Technol. Control doi: 10.1016/S0019-9958(80)90156-4 – volume: 23 start-page: 2039 issue: 5 year: 2019 end-page: 2051 ident: CR52 article-title: Intuitionistic center-free FCM clustering for MR brain image segmentation publication-title: IEEE J. Biomed. Health Inform. doi: 10.1109/JBHI.2018.2884208 – year: 1969 ident: CR71 publication-title: Nonlinear Programming: A Unified Approach – volume: 180 year: 2021 ident: CR6 article-title: A high-frequency low-cost technique for measuring small-scale water level fluctuations using computer vision publication-title: Measurement doi: 10.1016/j.measurement.2021.109477 – volume: 24 start-page: 1550016 (1–24) issue: 5 year: 2015 ident: CR35 article-title: Possibilistic intuitionistic fuzzy c-means clustering algorithm for MRI brain image segmentation publication-title: Int. J. Artif. Intell. Tools doi: 10.1142/S0218213015500165 – volume: 19 start-page: 1328 issue: 5 year: 2010 end-page: 1337 ident: CR19 article-title: A robust fuzzy local information c-means clustering algorithm publication-title: IEEE Trans. Image Process. doi: 10.1109/TIP.2010.2040763 – volume: 5 start-page: 127 issue: 2 year: 2001 end-page: 142 ident: CR20 article-title: Interaction in the segmentation of medical images: a survey publication-title: Med. Image Anal. doi: 10.1016/S1361-8415(00)00041-4 – volume: 94 year: 2020 ident: CR69 article-title: Total Bregman divergence-based fuzzy local information c-means clustering for robust image segmentation publication-title: Appl. Soft Comput. doi: 10.1016/j.asoc.2020.106468 – volume: 22 start-page: 888 issue: 8 year: 2000 end-page: 905 ident: CR2 article-title: Normalized cuts and image segmentation publication-title: IEEE Trans. Pattern Anal. Mach. Intell. doi: 10.1109/34.868688 – volume: 78 start-page: 1 issue: 6 year: 2018 end-page: 25 ident: CR38 article-title: A modified intuitionistic fuzzy c-means clustering approach to segment human brain MRI image publication-title: Multimed. Tools Appl. doi: 10.1007/s11042-018-5954-0 – year: 1981 ident: CR23 publication-title: Pattern Recognition with Fuzzy Objective Function Algorithms doi: 10.1007/978-1-4757-0450-1 – volume: 13 start-page: 607 issue: 4 year: 2019 end-page: 614 ident: CR48 article-title: Rough intuitionistic type-2 fuzzy c-means clustering algorithm for MR image segmentation publication-title: IET Image Process. doi: 10.1049/iet-ipr.2018.5597 – ident: CR76 – volume: 19 start-page: 459 issue: 2 year: 2015 end-page: 470 ident: CR18 article-title: Intuitionistic fuzzy c-means clustering algorithm with neighborhood attraction in segmenting medical image publication-title: Soft Comput. doi: 10.1007/s00500-014-1264-2 – volume: 32 start-page: 1699 issue: 4 year: 2010 end-page: 1723 ident: CR74 article-title: A novel color image segmentation approach based on Neutrosophic set and modified fuzzy c-means publication-title: Circuits Syst. Signal Process. doi: 10.1007/s00034-012-9531-x – volume: 114 start-page: 505 issue: 3 year: 2000 end-page: 518 ident: CR64 article-title: Distances between intuitionistic fuzzy sets publication-title: Fuzzy Sets Syst. doi: 10.1016/S0165-0114(98)00244-9 – volume: 11 start-page: 1711 issue: 2 year: 2011 ident: 2319_CR30 publication-title: Appl. Soft Comput. doi: 10.1016/j.asoc.2010.05.005 – volume: 21 start-page: 580 issue: 4 year: 2010 ident: 2319_CR34 publication-title: . Syst. Eng. Electron. doi: 10.3969/j.issn.1004-4132.2010.04.009 – volume: 1 start-page: 98 issue: 2 year: 1993 ident: 2319_CR36 publication-title: IEEE Trans. Fuzzy Syst. doi: 10.1109/91.227387 – volume: 3 start-page: 45 issue: 1 year: 2008 ident: 2319_CR28 publication-title: Int. J. Bus. Intell. Data Min. doi: 10.1504/IJBIDM.2008.017975 – volume: 22 start-page: 1074 issue: 5 year: 2014 ident: 2319_CR46 publication-title: IEEE Trans. Fuzzy Syst. doi: 10.1109/TFUZZ.2013.2280141 – volume: 94 year: 2020 ident: 2319_CR69 publication-title: Appl. Soft Comput. doi: 10.1016/j.asoc.2020.106468 – ident: 2319_CR63 doi: 10.1109/CIMCA.2005.1631233 – volume-title: Nonlinear Programming: A Unified Approach year: 1969 ident: 2319_CR71 – volume: 23 start-page: 1390 issue: 5 year: 2013 ident: 2319_CR17 publication-title: Digit. Signal Process. doi: 10.1016/j.dsp.2013.07.005 – volume: 20 start-page: 256 issue: 4 year: 2018 ident: 2319_CR59 publication-title: Entropy doi: 10.3390/e20040256 – volume: 4 start-page: 153 issue: 3 year: 2015 ident: 2319_CR1 publication-title: Int. J. Eng. Adv. Technol. – ident: 2319_CR80 doi: 10.1109/TBDATA.2016.2622288 – volume: 541 start-page: 365 year: 2016 ident: 2319_CR10 publication-title: Recent Dev. Intell. Syst. Interact. Appl. doi: 10.1007/978-3-319-49568-2_52 – volume: 26 start-page: 861 issue: 4 year: 2016 ident: 2319_CR66 publication-title: Stats Comput. doi: 10.1007/s11222-015-9576-3 – volume: 40 start-page: 825 issue: 3 year: 2007 ident: 2319_CR27 publication-title: Pattern Recognit. doi: 10.1016/j.patcog.2006.07.011 – volume: 44 start-page: 236 issue: 3 year: 1980 ident: 2319_CR32 publication-title: Inf. Technol. Control doi: 10.1016/S0019-9958(80)90156-4 – volume: 9 start-page: 345 issue: 4 year: 2017 ident: 2319_CR37 publication-title: Int. J. Inf. Technol. doi: 10.1007/s41870-017-0039-2 – volume: 41 start-page: 4083 issue: 9 year: 2014 ident: 2319_CR79 publication-title: Expert Syst. Appl. doi: 10.1016/j.eswa.2014.01.003 – volume: 3 start-page: 58 issue: 3 year: 1974 ident: 2319_CR77 publication-title: J. Cybern. doi: 10.1080/01969727308546047 – ident: 2319_CR15 doi: 10.1109/SMC.2016.7844622 – volume-title: Total Bregman Divergence, a Robust Divergence Measure, and Its Applications year: 2011 ident: 2319_CR54 – volume: 23 start-page: 2039 issue: 5 year: 2019 ident: 2319_CR52 publication-title: IEEE J. Biomed. Health Inform. doi: 10.1109/JBHI.2018.2884208 – ident: 2319_CR76 doi: 10.1109/ICCV.2001.937655 – volume: 78 start-page: 12663 issue: 6 year: 2019 ident: 2319_CR78 publication-title: Multimed. Tools and Appl. doi: 10.1007/s11042-018-5954-0 – ident: 2319_CR26 doi: 10.1109/IEMBS.2003.1279866 – volume: 46 start-page: 543 issue: C year: 2015 ident: 2319_CR47 publication-title: Appl. Soft Comput. doi: 10.1016/j.asoc.2015.12.022 – volume: 187 year: 2021 ident: 2319_CR7 publication-title: Comput. Electron. Agric. doi: 10.1016/j.compag.2021.106237 – volume: 114 start-page: 505 issue: 3 year: 2000 ident: 2319_CR64 publication-title: Fuzzy Sets Syst. doi: 10.1016/S0165-0114(98)00244-9 – volume: 78 start-page: 1 issue: 6 year: 2018 ident: 2319_CR38 publication-title: Multimed. Tools Appl. doi: 10.1007/s11042-018-5954-0 – volume: 28 start-page: 1023 issue: 6 year: 2020 ident: 2319_CR42 publication-title: IEEE Trans. Fuzzy Syst. doi: 10.1109/TFUZZ.2020.2973121 – volume: 32 start-page: 1699 issue: 4 year: 2010 ident: 2319_CR74 publication-title: Circuits Syst. Signal Process. doi: 10.1007/s00034-012-9531-x – volume: 13 start-page: 607 issue: 4 year: 2019 ident: 2319_CR48 publication-title: IET Image Process. doi: 10.1049/iet-ipr.2018.5597 – volume: 33 start-page: 261 issue: 3 year: 2010 ident: 2319_CR16 publication-title: Artif. Intell. Rev. doi: 10.1007/s10462-010-9155-0 – volume: 5 start-page: 127 issue: 2 year: 2001 ident: 2319_CR20 publication-title: Med. Image Anal. doi: 10.1016/S1361-8415(00)00041-4 – volume: 19 start-page: 459 issue: 2 year: 2015 ident: 2319_CR18 publication-title: Soft Comput. doi: 10.1007/s00500-014-1264-2 – volume: 24 start-page: 4003 issue: 6 year: 2020 ident: 2319_CR41 publication-title: Soft Comput. doi: 10.1007/s00500-019-04169-y – volume: 20 start-page: 295 issue: 4 year: 2013 ident: 2319_CR60 publication-title: IEEE Signal Process. Lett. doi: 10.1109/LSP.2013.2244080 – volume: 22 start-page: 888 issue: 8 year: 2000 ident: 2319_CR2 publication-title: IEEE Trans. Pattern Anal. Mach. Intell. doi: 10.1109/34.868688 – volume: 19 start-page: 475 issue: 5 year: 1997 ident: 2319_CR73 publication-title: IEEE Trans. Pattern Anal. Mach. Intell. doi: 10.1109/34.589206 – volume: 67 start-page: 773 issue: 5 year: 1979 ident: 2319_CR22 publication-title: P. IEEE doi: 10.1109/PROC.1979.11327 – volume: 5 start-page: 221 issue: 4 year: 1979 ident: 2319_CR31 publication-title: Int. J. Gen. Syst. doi: 10.1080/03081077908547452 – volume: 24 start-page: 1550016 (1–24) issue: 5 year: 2015 ident: 2319_CR35 publication-title: Int. J. Artif. Intell. Tools doi: 10.1142/S0218213015500165 – volume: 44 start-page: 1750 year: 2011 ident: 2319_CR44 publication-title: Pattern Recognit. doi: 10.1016/j.patcog.2011.02.009 – volume: 19 start-page: 1328 issue: 5 year: 2010 ident: 2319_CR19 publication-title: IEEE Trans. Image Process. doi: 10.1109/TIP.2010.2040763 – year: 2018 ident: 2319_CR75 publication-title: Mach. Learn. Data Min. doi: 10.5772/intechopen.74514 – volume: 8 start-page: 338 issue: 3 year: 1965 ident: 2319_CR62 publication-title: Inf. Control doi: 10.1016/S0019-9958(65)90241-X – volume: 22 start-page: 901 issue: 3 year: 2020 ident: 2319_CR53 publication-title: Int. J. Fuzzy Syst. doi: 10.1007/s40815-020-00824-x – volume: 27 start-page: 513 issue: 4 year: 2018 ident: 2319_CR8 publication-title: Civ. Eng. J. doi: 10.14311/CEJ.2018.04.0041 – volume: 35 start-page: 5255 issue: 5 year: 2018 ident: 2319_CR49 publication-title: J. Intell. Fuzzy Syst. doi: 10.3233/JIFS-169809 – volume: 22 start-page: 573 issue: 2 year: 2013 ident: 2319_CR70 publication-title: IEEE Trans. Image Process. doi: 10.1109/TIP.2012.2219547 – volume: 25 start-page: 1469 issue: 6 year: 2014 ident: 2319_CR12 publication-title: Mach. Vis. Appl. doi: 10.1007/s00138-014-0606-5 – volume: 21 start-page: 193 issue: 3 year: 2002 ident: 2319_CR24 publication-title: IEEE Trans. Med. Imaging doi: 10.1109/42.996338 – volume: 97 year: 2020 ident: 2319_CR61 publication-title: Digit. Signal Process. doi: 10.1016/j.dsp.2019.102615 – volume: 34 start-page: 1907 issue: 4 year: 2004 ident: 2319_CR25 publication-title: IEEE Trans. Syst. Man Cybern. doi: 10.1109/TSMCB.2004.831165 – volume: 7 issue: 24 year: 2019 ident: 2319_CR39 publication-title: ICST Trans. Scalable Inf. Syst. doi: 10.4108/eai.13-7-2018.159622 – ident: 2319_CR11 doi: 10.1109/CCIP.2016.7802852 – volume: 27 start-page: 387 issue: 2 year: 2018 ident: 2319_CR50 publication-title: IEEE T. Fuzzy Syst. doi: 10.1109/TFUZZ.2018.2852289 – volume: 40 start-page: 1890 issue: 09 year: 2019 ident: 2319_CR57 publication-title: Acta Armamentarii doi: 10.3969/j.issn.1000-1093.2019.09.014(inChinese) – volume: 2 start-page: 1 issue: 1 year: 1980 ident: 2319_CR72 publication-title: IEEE Trans. Pattern Anal. Mach. Intell. doi: 10.1109/tpami.1980.4766964 – volume: 453 start-page: 85 year: 2021 ident: 2319_CR5 publication-title: Neurocomputing doi: 10.1016/j.neucom.2021.04.094 – volume: 7 start-page: 360 issue: 2 year: 2014 ident: 2319_CR33 publication-title: Int. J. Comput. Int. Sys. doi: 10.1080/18756891.2013.865830 – volume: 31 start-page: 2864 issue: 9 year: 2014 ident: 2319_CR45 publication-title: Appl. Res. Comput. doi: 10.3969/j.issn.1001-3695.2014.09.073(inChinese) – volume: 30 start-page: 475 issue: 2 year: 2011 ident: 2319_CR56 publication-title: IEEE Trans. Med. Imaging doi: 10.1109/TMI.2010.2086464 – volume: 39 start-page: 1097 issue: 1 year: 2020 ident: 2319_CR40 publication-title: J. Intell. Fuzzy Syst. doi: 10.3233/JIFS-192005 – volume: 75 start-page: 232 issue: 75 year: 2018 ident: 2319_CR58 publication-title: Digit. Signal Process. doi: 10.1016/j.dsp.2018.01.008 – volume: 312 start-page: 296 year: 2018 ident: 2319_CR51 publication-title: Neurocomputing doi: 10.1016/j.neucom.2018.05.116 – ident: 2319_CR9 doi: 10.1109/ICComm.2016.7528317 – volume: 34 start-page: 2407 issue: 12 year: 2012 ident: 2319_CR55 publication-title: IEEE Trans. Pattern Anal. Mach. Intell. doi: 10.1109/tpami.2012.44 – volume: 34 start-page: 1329 issue: 12 year: 2013 ident: 2319_CR21 publication-title: Pattern Recognit. Lett. doi: 10.1016/j.patrec.2013.04.021 – volume: 59 start-page: 36 year: 2019 ident: 2319_CR4 publication-title: Robot. Comput.-Integr. Manuf. doi: 10.1016/j.rcim.2019.03.001 – volume-title: Pattern Recognition with Fuzzy Objective Function Algorithms year: 1981 ident: 2319_CR23 doi: 10.1007/978-1-4757-0450-1 – volume: 11 start-page: 65 issue: 3 year: 2012 ident: 2319_CR43 publication-title: WSEAS Trans. Comput. – volume: 20 start-page: 87 issue: 1 year: 1986 ident: 2319_CR29 publication-title: Fuzzy Sets Syst. doi: 10.1016/S0165-0114(86)80034-3 – volume: 188 start-page: 316 issue: 2 year: 2010 ident: 2319_CR14 publication-title: J. Neurosci. Methods doi: 10.1016/j.jneumeth.2010.03.004 – volume: 7 start-page: 200 issue: 3 year: 1967 ident: 2319_CR67 publication-title: USSR Comput. Math. Math. Phys. doi: 10.1016/0041-5553(67)90040-7 – volume: 14 start-page: 237 issue: 4 year: 1996 ident: 2319_CR68 publication-title: Nieuw Archief voor Wiskunde – volume: 11 start-page: 1 year: 2020 ident: 2319_CR3 publication-title: Front Plant Sci. doi: 10.3389/fpls.2020.00510 – volume: 180 year: 2021 ident: 2319_CR6 publication-title: Measurement doi: 10.1016/j.measurement.2021.109477 – volume: 6 start-page: 1705 issue: 4 year: 2005 ident: 2319_CR65 publication-title: J. Mach. Learn. Res. doi: 10.1137/1.9781611972740.22 – volume: 20 start-page: 2007 issue: 7 year: 2011 ident: 2319_CR13 publication-title: IEEE Trans. Image Process. doi: 10.1109/tip.2011.2146190
SSID	ssj0017749
Score	2.3506374
Snippet	Aiming at the shortcoming of existing robust intuitionistic fuzzy clustering and its variant algorithms in the presence of high noise, we will explore a novel...
SourceID	proquest crossref springer
SourceType	Aggregation Database Enrichment Source Index Database Publisher
StartPage	149
SubjectTerms	Algorithms Artificial Intelligence Clustering Computer Graphics Computer Science Divergence Euclidean geometry Fuzzy sets Genetic algorithms Image Processing and Computer Vision Image segmentation Neighborhoods Noise reduction Noise sensitivity Original Article Pixels Robustness (mathematics) Set theory Spatial data Statistical analysis Vision systems
SummonAdditionalLinks	– databaseName: ProQuest advanced technologies & aerospace journals dbid: P5Z link: http://cvtisr.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwpV07T8MwELZ4DTDwRhQK8sAGFnk1sScECAQLYgCpYon8CkKCFJoUCX4HP5g712kLEl1Ynfhk5S53n-277wg5SGIbZ6ZjmNKRYonRBVPKFCwyIjKpTYvUDptNZDc3vNsVt_7ArfJplY1PdI7a9DSekR9HsK_gIkp5ePL6xrBrFN6u-hYas2Q-jADrgz3fdh5GtwgAbRz8hZkMKz590YwrnXNcdQwTFJABTTD-MzCN0eavC1IXdy5X_rviVbLsESc9HZrIGpmx5TpZmuAh3CBf1xB5XO6Wo22mxeDz84N6TlUcZqaPXpHWPcDq9KxvH19kSQ3mdDgyTz9DPw-QdwFkUjzfpU22InURc1Ig1YhLsT1FXVEYpU8v4NhoBYJ9MVS5Se4vL-7Or5hv18A0fMCaadhZxjxRRZZKpNHXwoaZjLnKICAK2UkKkepAFhJsQ8dBYUNhpOKByWBLlugg3iJzZa-024SCGw2MNnGoOCCcSEmJ3VUDoUWqEh7KFgkbXeXac5njmp_zEQuz028O-s2dfnPeIoejOa9DJo-pb7cbpeb-r67ysUZb5Kgxi_Hjv6XtTJe2Sxaxi_3wZKdN5ur-wO6RBf1eP1X9fWfT36pxAZo priority: 102 providerName: ProQuest
Title	Intuitionistic fuzzy information-driven total Bregman divergence fuzzy clustering with multiple local information constraints for image segmentation
URI	https://link.springer.com/article/10.1007/s00371-021-02319-8 https://www.proquest.com/docview/2917892681
Volume	39
WOSCitedRecordID	wos000717889400001&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: PRVPQU databaseName: Advanced Technologies & Aerospace Database customDbUrl: eissn: 1432-2315 dateEnd: 20241214 omitProxy: false ssIdentifier: ssj0017749 issn: 0178-2789 databaseCode: P5Z dateStart: 19970201 isFulltext: true titleUrlDefault: https://search.proquest.com/hightechjournals providerName: ProQuest – providerCode: PRVPQU databaseName: Computer Science Database customDbUrl: eissn: 1432-2315 dateEnd: 20241214 omitProxy: false ssIdentifier: ssj0017749 issn: 0178-2789 databaseCode: K7- dateStart: 19970201 isFulltext: true titleUrlDefault: http://search.proquest.com/compscijour providerName: ProQuest – providerCode: PRVPQU databaseName: ProQuest Central customDbUrl: eissn: 1432-2315 dateEnd: 20241214 omitProxy: false ssIdentifier: ssj0017749 issn: 0178-2789 databaseCode: BENPR dateStart: 19970201 isFulltext: true titleUrlDefault: https://www.proquest.com/central providerName: ProQuest – providerCode: PRVAVX databaseName: Springer Journals - Owned customDbUrl: eissn: 1432-2315 dateEnd: 99991231 omitProxy: false ssIdentifier: ssj0017749 issn: 0178-2789 databaseCode: RSV dateStart: 19970101 isFulltext: true titleUrlDefault: https://link.springer.com/search?facet-content-type=%22Journal%22 providerName: Springer Nature
link	http://cvtisr.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwnV3JSgQxEC3cDnpwF8dlyMGbBnqb7uSooijCMLghXppsLYK2Mt0j6Hf4wVYy6XFBBb30IZ0UCZXUklS9AthKYhNnuqOpVJGkiVYFlVIXNNI80qlJi9QMi01k3S67uuI9nxRWNdHuzZOkk9SjZDeHLkdtSIHFLOOUjcOkBS-xdQtOzy5Hbwdo0DijN0T_yOZ5-lSZ72l8VkfvNuaXZ1GnbQ7n_jfPeZj11iXZHW6HBRgz5SLMNZUbiD_IizDzAYZwCV6PUfG40C2H2kyKwcvLM_GQqraZ6r4ViqR-QFOd7PXNzb0oibYhHQ7L049QdwMLu4A0ib3eJU2wInEK8yNBoqxZaqtT1BXBVnJ7j3KNVEjY50KVy3BxeHC-f0R9tQaqcJU1VehYxiyRRZYKi6KvuAkzETOZoT7kopMUPFWBKARuDRUHhQm5FpIFOkOPLFFBvAIT5UNpVoGgFA200nEoGRo4kRTCFlcNuOKpTFgoWhA2TMuVhzK3c77LRyDMjgk5MiF3TMhZC7ZHYx6HQB6_9t5o9kLuD3WVR-jaMh6lLGzBTsP7998_U1v7W_d1mLZF7YcXPRswUfcHZhOm1FN9W_XbMLl30O2dtmH8JKP47XWu2-4AvAHmdgD5
linkProvider	Springer Nature
linkToHtml	http://cvtisr.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMw1V1Lb9QwEB6VggQceKMuLeADnMBq4mQT-1AhXlVXLaseilRxCX4FVWqz7SYLan9Hf0d_IzNOsluQ6K0Hrk48cpzP4xl75huAV2nik9wNHTdWGJ46W3JjXMmFU8JlPisz3xabyMdjub-vdpfgos-FobDKXicGRe0mls7I1wX6FVKJTMbvjk84VY2i29W-hEYLi21_-gtdtnpj9An_72shNj_vfdziXVUBbhFuDbfoACUyNWWeaWJ7t8rHuU6kyVFvKz1MS5XZSJcaP8EmUelj5bSRkcvRc0htlKDcG3ATzQhFimB3-G1-a4GmVDC3caScMky7JJ2Qqhe48TgFRBDjmuLyz41wYd3-dSEb9rnN-__bDD2Ae51Fzd63S-AhLPnqEdy9xLP4GM5HuLOG2LRAS83K2dnZKes4Y6mZuylpfdZM0BdhH6b-x5GumKOYlUBW2vWwhzPilUCZjM6vWR-NyYJFcFkgs2R3U_mNpmbYyg6OUHGzGgV3yV7VE_h6LdPyFJarSeVXgOE2ETnrkthItOCE0Zqqx0bKqsykMtYDiHtsFLbjaqcxHxZzlumApwLxVAQ8FXIAb-Z9jlumkivfXutBVHRaqy4WCBrA2x6Gi8f_lvbsamkv4fbW3pedYmc03l6FOwJ7tadYa7DcTGf-OdyyP5uDevoirCcG368bnr8BgUVd8w
linkToPdf	http://cvtisr.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwpV1LTxwxDLZaiqr2UChQsZRHDr1BxLyYSY70sQK1WiG1RdxGeSIkGNDuLFL5Hf3BtTOZZYtapKrXTGJlZCe2Y_szwLsid3llDyzXJtO8sMZzra3nmZWZLV3pS9c1m6hGI3F2Jk_mqvhDtnsfkuxqGgilqWn3b6zfnxW-BaQ5TukFhF8muXgKzwpCQyN__evpLI6Axk0wgFP0lajmM5bN_JnG76rp3t58ECINmme49P97XoZX0epkh52YvIYnrlmBpb6jA4sHfAVezsETrsLPY1RIIaUroDkzP727-8Ei1CoNczumy5K112jCs_djd36lGmYp1SNgfMYV5nJKcAxIk9GzL-uTGFlQpPMEmSFzlbpWtBOGo-ziCu87NkHCsUaqWYPvw0_fPhzx2MWBG_zLlht0OHNRaF-VitD1jXRppXKhK9STUh0UXpYmUV6hyJg88S6VVmmR2Ao9tcIk-RtYaK4btw4Mb9fEGpunWqDhk2mlqOlqIo0sdSFSNYC0Z2BtIsQ57fmynoEzBybUyIQ6MKEWA9idrbnpAD4enb3Zy0UdD_ukztDlFTIrRTqAvV4O7j__ndrGv03fgecnH4f1l-PR57fwgvred29Bm7DQjqduCxbNbXsxGW-HM_ALPAkJVw
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=Intuitionistic+fuzzy+information-driven+total+Bregman+divergence+fuzzy+clustering+with+multiple+local+information+constraints+for+image+segmentation&rft.jtitle=The+Visual+computer&rft.au=Wu%2C+Chengmao&rft.au=Huang%2C+Congcong&rft.au=Zhang%2C+Jiajia&rft.date=2023-01-01&rft.pub=Springer+Berlin+Heidelberg&rft.issn=0178-2789&rft.eissn=1432-2315&rft.volume=39&rft.issue=1&rft.spage=149&rft.epage=181&rft_id=info:doi/10.1007%2Fs00371-021-02319-8&rft.externalDocID=10_1007_s00371_021_02319_8
thumbnail_l	http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/lc.gif&issn=0178-2789&client=summon
thumbnail_m	http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/mc.gif&issn=0178-2789&client=summon
thumbnail_s	http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/sc.gif&issn=0178-2789&client=summon