{"id":"https://openalex.org/W7139104449","doi":"https://doi.org/10.23919/icact68090.2026.11431364","title":"Macro Texture Detection Method for Road Surface Based on Machine Vision","display_name":"Macro Texture Detection Method for Road Surface Based on Machine Vision","publication_year":2026,"publication_date":"2026-02-08","ids":{"openalex":"https://openalex.org/W7139104449","doi":"https://doi.org/10.23919/icact68090.2026.11431364"},"language":null,"primary_location":{"id":"doi:10.23919/icact68090.2026.11431364","is_oa":false,"landing_page_url":"https://doi.org/10.23919/icact68090.2026.11431364","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2026 28th International Conference on Advanced Communications Technology (ICACT)","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/A5130182701","display_name":"Zhengwei LU","orcid":null},"institutions":[{"id":"https://openalex.org/I4210156034","display_name":"Sichuan Research Center of New Materials","ror":"https://ror.org/0587q0807","country_code":"CN","type":"facility","lineage":["https://openalex.org/I4210156034"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhengwei LU","raw_affiliation_strings":["Sichuan Chuanjiao Road and Bridge Construction Co., Ltd.,Chengdu,Sichuan,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Sichuan Chuanjiao Road and Bridge Construction Co., Ltd.,Chengdu,Sichuan,China","institution_ids":["https://openalex.org/I4210156034"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5129988271","display_name":"Md. Taherul Islam SHAWON","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Md. Taherul Islam SHAWON","raw_affiliation_strings":["Chang&#x0027;an University,Key Laboratory for Special Area Highway Engineering of Ministry of Education,Xi&#x0027;an,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Chang&#x0027;an University,Key Laboratory for Special Area Highway Engineering of Ministry of Education,Xi&#x0027;an,China","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100650088","display_name":"Qi Yang","orcid":"https://orcid.org/0000-0002-6214-6828"},"institutions":[{"id":"https://openalex.org/I4210156034","display_name":"Sichuan Research Center of New Materials","ror":"https://ror.org/0587q0807","country_code":"CN","type":"facility","lineage":["https://openalex.org/I4210156034"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhilin YANG","raw_affiliation_strings":["Sichuan Chuanjiao Road and Bridge Construction Co., Ltd.,Chengdu,Sichuan,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Sichuan Chuanjiao Road and Bridge Construction Co., Ltd.,Chengdu,Sichuan,China","institution_ids":["https://openalex.org/I4210156034"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5014810546","display_name":"Wenpeng Hu","orcid":null},"institutions":[{"id":"https://openalex.org/I4210156034","display_name":"Sichuan Research Center of New Materials","ror":"https://ror.org/0587q0807","country_code":"CN","type":"facility","lineage":["https://openalex.org/I4210156034"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Wenpeng HU","raw_affiliation_strings":["Sichuan Chuanjiao Road and Bridge Construction Co., Ltd.,Chengdu,Sichuan,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Sichuan Chuanjiao Road and Bridge Construction Co., Ltd.,Chengdu,Sichuan,China","institution_ids":["https://openalex.org/I4210156034"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5129883149","display_name":"Junjie NIU","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Junjie NIU","raw_affiliation_strings":["Chang&#x0027;an University,Key Laboratory for Special Area Highway Engineering of Ministry of Education,Xi&#x0027;an,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Chang&#x0027;an University,Key Laboratory for Special Area Highway Engineering of Ministry of Education,Xi&#x0027;an,China","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100354288","display_name":"Cheng Li","orcid":"https://orcid.org/0000-0003-1167-3609"},"institutions":[{"id":"https://openalex.org/I4210156034","display_name":"Sichuan Research Center of New Materials","ror":"https://ror.org/0587q0807","country_code":"CN","type":"facility","lineage":["https://openalex.org/I4210156034"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Cheng LI","raw_affiliation_strings":["Sichuan Chuanjiao Road and Bridge Construction Co., Ltd.,Chengdu,Sichuan,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Sichuan Chuanjiao Road and Bridge Construction Co., Ltd.,Chengdu,Sichuan,China","institution_ids":["https://openalex.org/I4210156034"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5130099892","display_name":"Yanjie ZHOU","orcid":null},"institutions":[{"id":"https://openalex.org/I4210156034","display_name":"Sichuan Research Center of New Materials","ror":"https://ror.org/0587q0807","country_code":"CN","type":"facility","lineage":["https://openalex.org/I4210156034"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yanjie ZHOU","raw_affiliation_strings":["Sichuan Chuanjiao Road and Bridge Construction Co., Ltd.,Chengdu,Sichuan,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Sichuan Chuanjiao Road and Bridge Construction Co., Ltd.,Chengdu,Sichuan,China","institution_ids":["https://openalex.org/I4210156034"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5111353475","display_name":"Shiyue Yin","orcid":null},"institutions":[{"id":"https://openalex.org/I4210156034","display_name":"Sichuan Research Center of New Materials","ror":"https://ror.org/0587q0807","country_code":"CN","type":"facility","lineage":["https://openalex.org/I4210156034"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Shiyue YIN","raw_affiliation_strings":["Sichuan Chuanjiao Road and Bridge Construction Co., Ltd.,Chengdu,Sichuan,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Sichuan Chuanjiao Road and Bridge Construction Co., Ltd.,Chengdu,Sichuan,China","institution_ids":["https://openalex.org/I4210156034"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"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":0.31413467,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"6"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11606","display_name":"Infrastructure Maintenance and Monitoring","score":0.8741999864578247,"subfield":{"id":"https://openalex.org/subfields/2205","display_name":"Civil and Structural Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T11606","display_name":"Infrastructure Maintenance and Monitoring","score":0.8741999864578247,"subfield":{"id":"https://openalex.org/subfields/2205","display_name":"Civil and Structural 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/T13049","display_name":"Surface Roughness and Optical Measurements","score":0.020400000736117363,"subfield":{"id":"https://openalex.org/subfields/2206","display_name":"Computational Mechanics"},"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/T11164","display_name":"Remote Sensing and LiDAR Applications","score":0.01759999990463257,"subfield":{"id":"https://openalex.org/subfields/2305","display_name":"Environmental Engineering"},"field":{"id":"https://openalex.org/fields/23","display_name":"Environmental Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/road-surface","display_name":"Road surface","score":0.5907999873161316},{"id":"https://openalex.org/keywords/preprocessor","display_name":"Preprocessor","score":0.5388000011444092},{"id":"https://openalex.org/keywords/machine-vision","display_name":"Machine vision","score":0.5329999923706055},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.5166000127792358},{"id":"https://openalex.org/keywords/data-pre-processing","display_name":"Data pre-processing","score":0.4846999943256378},{"id":"https://openalex.org/keywords/lidar","display_name":"Lidar","score":0.4706000089645386},{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.38589999079704285},{"id":"https://openalex.org/keywords/macro","display_name":"Macro","score":0.36489999294281006},{"id":"https://openalex.org/keywords/ranging","display_name":"Ranging","score":0.3628999888896942}],"concepts":[{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6456000208854675},{"id":"https://openalex.org/C2780042925","wikidata":"https://www.wikidata.org/wiki/Q1049667","display_name":"Road surface","level":2,"score":0.5907999873161316},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.5570999979972839},{"id":"https://openalex.org/C34736171","wikidata":"https://www.wikidata.org/wiki/Q918333","display_name":"Preprocessor","level":2,"score":0.5388000011444092},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5376999974250793},{"id":"https://openalex.org/C5339829","wikidata":"https://www.wikidata.org/wiki/Q1425977","display_name":"Machine vision","level":2,"score":0.5329999923706055},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.5166000127792358},{"id":"https://openalex.org/C10551718","wikidata":"https://www.wikidata.org/wiki/Q5227332","display_name":"Data pre-processing","level":2,"score":0.4846999943256378},{"id":"https://openalex.org/C51399673","wikidata":"https://www.wikidata.org/wiki/Q504027","display_name":"Lidar","level":2,"score":0.4706000089645386},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.38589999079704285},{"id":"https://openalex.org/C166955791","wikidata":"https://www.wikidata.org/wiki/Q629579","display_name":"Macro","level":2,"score":0.36489999294281006},{"id":"https://openalex.org/C115051666","wikidata":"https://www.wikidata.org/wiki/Q6522493","display_name":"Ranging","level":2,"score":0.3628999888896942},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.35679998993873596},{"id":"https://openalex.org/C99498987","wikidata":"https://www.wikidata.org/wiki/Q2210247","display_name":"Noise (video)","level":3,"score":0.352400004863739},{"id":"https://openalex.org/C48044578","wikidata":"https://www.wikidata.org/wiki/Q727490","display_name":"Scalability","level":2,"score":0.3357999920845032},{"id":"https://openalex.org/C131979681","wikidata":"https://www.wikidata.org/wiki/Q1899648","display_name":"Point cloud","level":2,"score":0.33239999413490295},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3303999900817871},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.32260000705718994},{"id":"https://openalex.org/C94296324","wikidata":"https://www.wikidata.org/wiki/Q2234301","display_name":"Skid (aerodynamics)","level":2,"score":0.30469998717308044},{"id":"https://openalex.org/C81074085","wikidata":"https://www.wikidata.org/wiki/Q366872","display_name":"Motion planning","level":3,"score":0.2980000078678131},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.2948000133037567},{"id":"https://openalex.org/C9417928","wikidata":"https://www.wikidata.org/wiki/Q1070689","display_name":"Image processing","level":3,"score":0.289000004529953},{"id":"https://openalex.org/C102290492","wikidata":"https://www.wikidata.org/wiki/Q7575045","display_name":"Speckle pattern","level":2,"score":0.28859999775886536},{"id":"https://openalex.org/C36464697","wikidata":"https://www.wikidata.org/wiki/Q451553","display_name":"Visualization","level":2,"score":0.28760001063346863},{"id":"https://openalex.org/C124504099","wikidata":"https://www.wikidata.org/wiki/Q56933","display_name":"Image segmentation","level":3,"score":0.28439998626708984},{"id":"https://openalex.org/C33954974","wikidata":"https://www.wikidata.org/wiki/Q486494","display_name":"Sensor fusion","level":2,"score":0.2840999960899353},{"id":"https://openalex.org/C34413123","wikidata":"https://www.wikidata.org/wiki/Q170978","display_name":"Robotics","level":3,"score":0.2687000036239624},{"id":"https://openalex.org/C141349535","wikidata":"https://www.wikidata.org/wiki/Q1361664","display_name":"Laser scanning","level":3,"score":0.2614000141620636},{"id":"https://openalex.org/C123403432","wikidata":"https://www.wikidata.org/wiki/Q654068","display_name":"Visibility","level":2,"score":0.25679999589920044},{"id":"https://openalex.org/C79061980","wikidata":"https://www.wikidata.org/wiki/Q941680","display_name":"Inertial measurement unit","level":2,"score":0.2558000087738037}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.23919/icact68090.2026.11431364","is_oa":false,"landing_page_url":"https://doi.org/10.23919/icact68090.2026.11431364","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2026 28th International Conference on Advanced Communications Technology (ICACT)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.6221002340316772,"display_name":"Industry, innovation and infrastructure","id":"https://metadata.un.org/sdg/9"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":20,"referenced_works":["https://openalex.org/W2133498391","https://openalex.org/W2200675143","https://openalex.org/W2507522151","https://openalex.org/W2515602771","https://openalex.org/W2553914821","https://openalex.org/W2588612844","https://openalex.org/W2792469128","https://openalex.org/W2800580548","https://openalex.org/W2958981985","https://openalex.org/W3087764524","https://openalex.org/W4306743898","https://openalex.org/W4311183462","https://openalex.org/W4323816641","https://openalex.org/W4399379696","https://openalex.org/W4404787824","https://openalex.org/W4407173089","https://openalex.org/W4407755414","https://openalex.org/W4409002007","https://openalex.org/W4411011451","https://openalex.org/W4411690736"],"related_works":[],"abstract_inverted_index":{"Road":[0],"surface":[1,6,160],"macro":[2,93],"texture,":[3],"characterized":[4],"by":[5,61],"irregularities":[7],"with":[8],"wavelengths":[9],"ranging":[10],"from":[11,123],"0.5":[12],"mm":[13],"to":[14,114,168,175],"50":[15],"mm,":[16],"plays":[17],"a":[18,85,187],"vital":[19],"role":[20],"in":[21],"determining":[22],"pavement":[23],"performance":[24],"and":[25,43,54,68,87,105,118,126,134,142,165,180,193],"overall":[26],"roadway":[27],"safety.":[28],"It":[29],"significantly":[30],"affects":[31],"key":[32],"functional":[33],"aspects":[34],"such":[35,155],"as":[36,84],"skid":[37],"resistance,":[38],"drainage":[39],"capability,":[40],"tire-pavement":[41],"interaction,":[42],"noise":[44],"emission.":[45],"Conventional":[46],"measurement":[47,136,140],"techniques,":[48],"including":[49],"the":[50,79,152],"sand":[51],"patch":[52],"test":[53],"laser":[55],"profilometry,":[56],"although":[57],"precise,":[58],"are":[59],"limited":[60],"high":[62],"operational":[63],"costs,":[64],"intensive":[65],"labor":[66],"requirements,":[67],"restricted":[69],"spatial":[70],"coverage.":[71],"To":[72],"address":[73],"these":[74],"limitations,":[75],"this":[76],"study":[77],"investigates":[78],"application":[80],"of":[81,120,132,154,196],"machine":[82,106,183],"vision":[83],"non-contact":[86],"fully":[88],"automated":[89],"approach":[90],"for":[91,157],"quantitative":[92],"texture":[94,121],"evaluation.":[95],"The":[96,130,149],"proposed":[97],"framework":[98],"combines":[99],"high-resolution":[100],"imaging,":[101],"advanced":[102],"preprocessing":[103],"methods,":[104],"learning":[107],"algorithms,":[108],"particularly":[109],"convolutional":[110],"neural":[111],"networks":[112],"(CNNs),":[113],"enable":[115],"reliable":[116],"extraction":[117],"classification":[119],"features":[122],"both":[124],"twodimensional":[125],"three-dimensional":[127],"data":[128,178],"sources.":[129],"integration":[131],"LiDAR":[133],"inertial":[135],"sensors":[137],"further":[138],"enhances":[139],"precision":[141],"system":[143],"stability":[144],"under":[145],"varying":[146],"environmental":[147,176],"conditions.":[148],"results":[150],"highlight":[151],"potential":[153],"systems":[156],"real-time,":[158],"vehicle-mounted":[159],"inspection,":[161],"offering":[162],"superior":[163],"scalability":[164],"cost-effectiveness":[166],"compared":[167],"traditional":[169],"methods.":[170],"Despite":[171],"persistent":[172],"challenges":[173],"related":[174],"variability,":[177],"annotation,":[179],"computational":[181],"complexity,":[182],"vision-based":[184],"solutions":[185],"represent":[186],"promising":[188],"advancement":[189],"toward":[190],"intelligent,":[191],"data-driven,":[192],"sustainable":[194],"management":[195],"road":[197],"infrastructure.":[198]},"counts_by_year":[],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2026-03-20T00:00:00"}
