{"id":"https://openalex.org/W2528431467","doi":"https://doi.org/10.1109/icite.2016.7581316","title":"Tunnel moving target detection based on local structure of image and gray scale information","display_name":"Tunnel moving target detection based on local structure of image and gray scale information","publication_year":2016,"publication_date":"2016-08-01","ids":{"openalex":"https://openalex.org/W2528431467","doi":"https://doi.org/10.1109/icite.2016.7581316","mag":"2528431467"},"language":"en","primary_location":{"id":"doi:10.1109/icite.2016.7581316","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icite.2016.7581316","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2016 IEEE International Conference on Intelligent Transportation Engineering (ICITE)","raw_type":"proceedings-article"},"type":"conference-paper","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/A5086740564","display_name":"Haiyang Yu","orcid":"https://orcid.org/0000-0002-0704-7077"},"institutions":[{"id":"https://openalex.org/I1302611135","display_name":"Ministry of Public Security of the People's Republic of China","ror":"https://ror.org/00bt9we26","country_code":"CN","type":"government","lineage":["https://openalex.org/I1302611135"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Haiyang Yu","raw_affiliation_strings":["People's Republic of China, Key Laboratory of Urban ITS Technology Optimization and Integration Ministry of Public Security, Hefei, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"People's Republic of China, Key Laboratory of Urban ITS Technology Optimization and Integration Ministry of Public Security, Hefei, China","institution_ids":["https://openalex.org/I1302611135"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5108755630","display_name":"Yawen Hu","orcid":null},"institutions":[{"id":"https://openalex.org/I82880672","display_name":"Beihang University","ror":"https://ror.org/00wk2mp56","country_code":"CN","type":"education","lineage":["https://openalex.org/I82880672"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yawen Hu","raw_affiliation_strings":["School of Transportation Science and Engineering, Beihang University, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Transportation Science and Engineering, Beihang University, Beijing, China","institution_ids":["https://openalex.org/I82880672"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101815817","display_name":"Hongyu Guo","orcid":"https://orcid.org/0000-0002-6969-5424"},"institutions":[{"id":"https://openalex.org/I82880672","display_name":"Beihang University","ror":"https://ror.org/00wk2mp56","country_code":"CN","type":"education","lineage":["https://openalex.org/I82880672"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Hongyu Guo","raw_affiliation_strings":["Infrastructure Systems and Safety Control, Beihang University, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Infrastructure Systems and Safety Control, Beihang University, Beijing, China","institution_ids":["https://openalex.org/I82880672"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5101738423","display_name":"Lin Fang","orcid":"https://orcid.org/0000-0002-1991-8626"},"institutions":[{"id":"https://openalex.org/I4210108204","display_name":"China Electronic Information Industry Development","ror":"https://ror.org/01mbbxx50","country_code":"CN","type":"other","lineage":["https://openalex.org/I4210108204","https://openalex.org/I890469752"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Lin Fang","raw_affiliation_strings":["Information Industry Co. Ltd., Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Information Industry Co. Ltd., Beijing, China","institution_ids":["https://openalex.org/I4210108204"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"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":0.10705937,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"25","issue":null,"first_page":"103","last_page":"107"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10331","display_name":"Video Surveillance and Tracking Methods","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/T10331","display_name":"Video Surveillance and Tracking Methods","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/T14257","display_name":"Advanced Measurement and Detection Methods","score":0.994700014591217,"subfield":{"id":"https://openalex.org/subfields/2208","display_name":"Electrical and Electronic Engineering"},"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/T12597","display_name":"Fire Detection and Safety Systems","score":0.9911999702453613,"subfield":{"id":"https://openalex.org/subfields/2213","display_name":"Safety, Risk, Reliability and Quality"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.8307144641876221},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.7985787391662598},{"id":"https://openalex.org/keywords/grayscale","display_name":"Grayscale","score":0.6384379863739014},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6180447340011597},{"id":"https://openalex.org/keywords/pixel","display_name":"Pixel","score":0.5392234921455383},{"id":"https://openalex.org/keywords/brightness","display_name":"Brightness","score":0.535000205039978},{"id":"https://openalex.org/keywords/object-detection","display_name":"Object detection","score":0.5019171237945557},{"id":"https://openalex.org/keywords/motion-detection","display_name":"Motion detection","score":0.48622456192970276},{"id":"https://openalex.org/keywords/similarity-measure","display_name":"Similarity measure","score":0.46777382493019104},{"id":"https://openalex.org/keywords/image-segmentation","display_name":"Image segmentation","score":0.4135955572128296},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4126676917076111},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.3446108102798462},{"id":"https://openalex.org/keywords/motion","display_name":"Motion (physics)","score":0.1958027482032776}],"concepts":[{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.8307144641876221},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.7985787391662598},{"id":"https://openalex.org/C78201319","wikidata":"https://www.wikidata.org/wiki/Q685727","display_name":"Grayscale","level":3,"score":0.6384379863739014},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6180447340011597},{"id":"https://openalex.org/C160633673","wikidata":"https://www.wikidata.org/wiki/Q355198","display_name":"Pixel","level":2,"score":0.5392234921455383},{"id":"https://openalex.org/C125245961","wikidata":"https://www.wikidata.org/wiki/Q221656","display_name":"Brightness","level":2,"score":0.535000205039978},{"id":"https://openalex.org/C2776151529","wikidata":"https://www.wikidata.org/wiki/Q3045304","display_name":"Object detection","level":3,"score":0.5019171237945557},{"id":"https://openalex.org/C2780624872","wikidata":"https://www.wikidata.org/wiki/Q852453","display_name":"Motion detection","level":3,"score":0.48622456192970276},{"id":"https://openalex.org/C2776517306","wikidata":"https://www.wikidata.org/wiki/Q29017317","display_name":"Similarity measure","level":2,"score":0.46777382493019104},{"id":"https://openalex.org/C124504099","wikidata":"https://www.wikidata.org/wiki/Q56933","display_name":"Image segmentation","level":3,"score":0.4135955572128296},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4126676917076111},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.3446108102798462},{"id":"https://openalex.org/C104114177","wikidata":"https://www.wikidata.org/wiki/Q79782","display_name":"Motion (physics)","level":2,"score":0.1958027482032776},{"id":"https://openalex.org/C120665830","wikidata":"https://www.wikidata.org/wiki/Q14620","display_name":"Optics","level":1,"score":0.0},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icite.2016.7581316","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icite.2016.7581316","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2016 IEEE International Conference on Intelligent Transportation Engineering (ICITE)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Sustainable cities and communities","id":"https://metadata.un.org/sdg/11","score":0.5199999809265137}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":14,"referenced_works":["https://openalex.org/W1461293587","https://openalex.org/W1512617924","https://openalex.org/W1578285471","https://openalex.org/W2006513420","https://openalex.org/W2027945172","https://openalex.org/W2054883883","https://openalex.org/W2071860582","https://openalex.org/W2078608338","https://openalex.org/W2115415549","https://openalex.org/W2122676258","https://openalex.org/W2130293653","https://openalex.org/W2751023760","https://openalex.org/W2994436332","https://openalex.org/W4248936881"],"related_works":["https://openalex.org/W115686965","https://openalex.org/W2768918307","https://openalex.org/W2110031805","https://openalex.org/W2040020606","https://openalex.org/W2387055199","https://openalex.org/W2313061941","https://openalex.org/W3162303681","https://openalex.org/W3204216905","https://openalex.org/W2911525783","https://openalex.org/W4376454785"],"abstract_inverted_index":{"Tunnel":[0],"moving":[1,31,91,131,156],"target":[2,113,121,132],"detection":[3,18,39,133,141],"is":[4,51,61,105],"subject":[5],"to":[6,107,115,128],"the":[7,15,59,64,69,74,87,95,109,112,117,120,124,130,140,144,148,155],"influence":[8,96],"of":[9,45,58,90,97,111,119,143],"light":[10],"condition":[11],"and":[12,47,67,73,93,123,127,147],"motion":[13,17],"blur,":[14],"traditional":[16],"method":[19,40,142],"based":[20,41],"on":[21,42],"pixel":[22],"points":[23],"can":[24,152],"not":[25],"be":[26],"very":[27],"good":[28],"at":[29],"segmenting":[30],"target.":[32],"To":[33],"solve":[34],"this":[35],"problem,":[36],"frame":[37],"difference":[38,56],"local":[43,54],"structure":[44,146],"image":[46,60,98],"gray":[48,75,102,149],"level":[49,150],"information":[50,57,151],"proposed.":[52],"The":[53,81,101,135],"mean":[55],"calculated":[62],"by":[63],"improved":[65],"algorithm,":[66],"then":[68],"similarity":[70,82],"measure":[71,77,83],"function":[72,78,84,104],"scale":[76,103],"are":[79],"constructed.":[80],"effectively":[85,153],"describes":[86],"structural":[88],"features":[89],"objects,":[92],"reduces":[94],"background":[99,125],"information.":[100],"better":[106],"highlight":[108],"contrast":[110],"brightness,":[114],"increase":[116],"division":[118],"area":[122],"parts,":[126],"realize":[129],"correctly.":[134],"experimental":[136],"results":[137],"show":[138],"that":[139],"fusion":[145],"segment":[154],"object.":[157]},"counts_by_year":[],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2025-10-10T00:00:00"}