{"id":"https://openalex.org/W2535084101","doi":"https://doi.org/10.1109/fskd.2016.7603416","title":"A robust edge indicator employing nonlocal structure tensor","display_name":"A robust edge indicator employing nonlocal structure tensor","publication_year":2016,"publication_date":"2016-08-01","ids":{"openalex":"https://openalex.org/W2535084101","doi":"https://doi.org/10.1109/fskd.2016.7603416","mag":"2535084101"},"language":"en","primary_location":{"id":"doi:10.1109/fskd.2016.7603416","is_oa":false,"landing_page_url":"https://doi.org/10.1109/fskd.2016.7603416","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2016 12th International Conference on Natural Computation, Fuzzy Systems and Knowledge Discovery (ICNC-FSKD)","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":false,"oa_status":"closed","oa_url":null,"any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5069833912","display_name":"Xianghua Tan","orcid":"https://orcid.org/0000-0002-8814-2497"},"institutions":[{"id":"https://openalex.org/I4210101451","display_name":"Nanjing University of Industry Technology","ror":"https://ror.org/00qf07q44","country_code":"CN","type":"facility","lineage":["https://openalex.org/I4210101451"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xianghua Tan","raw_affiliation_strings":["College of Arts and Sciences, Nanjing Vocational Institute of Industry Technology, Nanjing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"College of Arts and Sciences, Nanjing Vocational Institute of Industry Technology, Nanjing, China","institution_ids":["https://openalex.org/I4210101451"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5084996912","display_name":"Tao Tang","orcid":"https://orcid.org/0000-0002-9071-137X"},"institutions":[{"id":"https://openalex.org/I76569877","display_name":"Southeast University","ror":"https://ror.org/04ct4d772","country_code":"CN","type":"education","lineage":["https://openalex.org/I76569877"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Tao Tang","raw_affiliation_strings":["School of Automation, Southeast University, Nanjing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Automation, Southeast University, Nanjing, China","institution_ids":["https://openalex.org/I76569877"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.10706293,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"1605","last_page":"1608"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10052","display_name":"Medical Image Segmentation Techniques","score":0.9995999932289124,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T10052","display_name":"Medical Image Segmentation Techniques","score":0.9995999932289124,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T13114","display_name":"Image Processing Techniques and Applications","score":0.9991000294685364,"subfield":{"id":"https://openalex.org/subfields/2214","display_name":"Media Technology"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T11105","display_name":"Advanced Image Processing Techniques","score":0.9990000128746033,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/structure-tensor","display_name":"Structure tensor","score":0.9108000993728638},{"id":"https://openalex.org/keywords/tensor","display_name":"Tensor (intrinsic definition)","score":0.7633869647979736},{"id":"https://openalex.org/keywords/enhanced-data-rates-for-gsm-evolution","display_name":"Enhanced Data Rates for GSM Evolution","score":0.7152574062347412},{"id":"https://openalex.org/keywords/eigenvalues-and-eigenvectors","display_name":"Eigenvalues and eigenvectors","score":0.6857441663742065},{"id":"https://openalex.org/keywords/noise","display_name":"Noise (video)","score":0.5537289381027222},{"id":"https://openalex.org/keywords/pixel","display_name":"Pixel","score":0.45313990116119385},{"id":"https://openalex.org/keywords/matrix","display_name":"Matrix (chemical analysis)","score":0.44122105836868286},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.4396456182003021},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.4030013978481293},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.3671637177467346},{"id":"https://openalex.org/keywords/geometry","display_name":"Geometry","score":0.20548716187477112},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.19495359063148499},{"id":"https://openalex.org/keywords/physics","display_name":"Physics","score":0.17007502913475037},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.12944760918617249},{"id":"https://openalex.org/keywords/materials-science","display_name":"Materials science","score":0.06949764490127563}],"concepts":[{"id":"https://openalex.org/C113315163","wikidata":"https://www.wikidata.org/wiki/Q7625159","display_name":"Structure tensor","level":3,"score":0.9108000993728638},{"id":"https://openalex.org/C155281189","wikidata":"https://www.wikidata.org/wiki/Q3518150","display_name":"Tensor (intrinsic definition)","level":2,"score":0.7633869647979736},{"id":"https://openalex.org/C162307627","wikidata":"https://www.wikidata.org/wiki/Q204833","display_name":"Enhanced Data Rates for GSM Evolution","level":2,"score":0.7152574062347412},{"id":"https://openalex.org/C158693339","wikidata":"https://www.wikidata.org/wiki/Q190524","display_name":"Eigenvalues and eigenvectors","level":2,"score":0.6857441663742065},{"id":"https://openalex.org/C99498987","wikidata":"https://www.wikidata.org/wiki/Q2210247","display_name":"Noise (video)","level":3,"score":0.5537289381027222},{"id":"https://openalex.org/C160633673","wikidata":"https://www.wikidata.org/wiki/Q355198","display_name":"Pixel","level":2,"score":0.45313990116119385},{"id":"https://openalex.org/C106487976","wikidata":"https://www.wikidata.org/wiki/Q685816","display_name":"Matrix (chemical analysis)","level":2,"score":0.44122105836868286},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.4396456182003021},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.4030013978481293},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.3671637177467346},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.20548716187477112},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.19495359063148499},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.17007502913475037},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.12944760918617249},{"id":"https://openalex.org/C192562407","wikidata":"https://www.wikidata.org/wiki/Q228736","display_name":"Materials science","level":0,"score":0.06949764490127563},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0},{"id":"https://openalex.org/C159985019","wikidata":"https://www.wikidata.org/wiki/Q181790","display_name":"Composite material","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/fskd.2016.7603416","is_oa":false,"landing_page_url":"https://doi.org/10.1109/fskd.2016.7603416","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2016 12th International Conference on Natural Computation, Fuzzy Systems and Knowledge Discovery (ICNC-FSKD)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.6100000143051147,"display_name":"Sustainable cities and communities","id":"https://metadata.un.org/sdg/11"}],"awards":[],"funders":[{"id":"https://openalex.org/F4320322769","display_name":"Natural Science Foundation of Jiangsu Province","ror":"https://ror.org/01h0zpd94"},{"id":"https://openalex.org/F4320328118","display_name":"Nanjing Institute of Industry Technology","ror":"https://ror.org/00qf07q44"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":15,"referenced_works":["https://openalex.org/W1545934923","https://openalex.org/W1979760215","https://openalex.org/W2013756948","https://openalex.org/W2014518518","https://openalex.org/W2015338231","https://openalex.org/W2028955956","https://openalex.org/W2029356963","https://openalex.org/W2038126130","https://openalex.org/W2058119580","https://openalex.org/W2058990475","https://openalex.org/W2076168919","https://openalex.org/W2085135890","https://openalex.org/W2104804805","https://openalex.org/W2139129723","https://openalex.org/W6632552969"],"related_works":["https://openalex.org/W2067272521","https://openalex.org/W89301254","https://openalex.org/W2623954137","https://openalex.org/W2015754241","https://openalex.org/W1997494252","https://openalex.org/W3174244707","https://openalex.org/W3206725971","https://openalex.org/W2052072320","https://openalex.org/W2385280846","https://openalex.org/W2944675036"],"abstract_inverted_index":{"In":[0,17],"this":[1],"paper,":[2],"we":[3],"propose":[4],"a":[5,20,49,60,65],"robust":[6,32],"edge":[7,52,63,75],"indicator":[8,53,76],"employing":[9],"two":[10],"eigenvalues":[11],"of":[12,81,88],"nonlocal":[13,22,38,46],"structure":[14,23,29,47],"tensor":[15,24,30],"matrix.":[16],"our":[18,89],"method,":[19],"new":[21,50],"is":[25,31,54,91],"first":[26],"constructed.":[27],"This":[28],"to":[33,93],"noise,":[34],"which":[35,56],"inherits":[36],"from":[37,64],"means":[39],"algorithm.":[40],"Furthermore,":[41],"based":[42],"on":[43],"the":[44,73,79,82,86,94],"constructed":[45],"tensor,":[48],"and":[51],"built,":[55],"can":[57,77],"effectively":[58],"differentiate":[59],"pixel":[61,66],"at":[62],"in":[67],"flat":[68],"region":[69],"with":[70],"noise.":[71],"Moreover,":[72],"proposed":[74],"characteristic":[78],"strength":[80],"edges.":[83],"By":[84],"experiments,":[85],"results":[87],"method":[90],"superior":[92],"gradient's":[95],"results.":[96]},"counts_by_year":[],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}
