{"id":"https://openalex.org/W2896894644","doi":"https://doi.org/10.1109/access.2018.2875889","title":"Image-Based Crack Detection Using Crack Width Transform (CWT) Algorithm","display_name":"Image-Based Crack Detection Using Crack Width Transform (CWT) Algorithm","publication_year":2018,"publication_date":"2018-01-01","ids":{"openalex":"https://openalex.org/W2896894644","doi":"https://doi.org/10.1109/access.2018.2875889","mag":"2896894644"},"language":"en","primary_location":{"id":"doi:10.1109/access.2018.2875889","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2018.2875889","pdf_url":null,"source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://doi.org/10.1109/access.2018.2875889","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5101637014","display_name":"Hyun-Woo Cho","orcid":"https://orcid.org/0000-0002-5822-5865"},"institutions":[{"id":"https://openalex.org/I88761825","display_name":"Korea University of Science and Technology","ror":"https://ror.org/000qzf213","country_code":"KR","type":"education","lineage":["https://openalex.org/I88761825"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Hyunwoo Cho","raw_affiliation_strings":["Department of Robotics and Virtual Engineering, Korea University of Science and Technology, Daejeon, South Korea"],"raw_orcid":"https://orcid.org/0000-0002-5822-5865","affiliations":[{"raw_affiliation_string":"Department of Robotics and Virtual Engineering, Korea University of Science and Technology, Daejeon, South Korea","institution_ids":["https://openalex.org/I88761825"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5102961322","display_name":"Hyuk-Jin Yoon","orcid":"https://orcid.org/0000-0003-4843-7191"},"institutions":[{"id":"https://openalex.org/I88761825","display_name":"Korea University of Science and Technology","ror":"https://ror.org/000qzf213","country_code":"KR","type":"education","lineage":["https://openalex.org/I88761825"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Hyuk-Jin Yoon","raw_affiliation_strings":["Department of Robotics and Virtual Engineering, Korea University of Science and Technology, Daejeon, South Korea"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Robotics and Virtual Engineering, Korea University of Science and Technology, Daejeon, South Korea","institution_ids":["https://openalex.org/I88761825"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5036819957","display_name":"Ju-Yeong Jung","orcid":"https://orcid.org/0000-0002-6038-0100"},"institutions":[{"id":"https://openalex.org/I4210161173","display_name":"Korea Railroad Research Institute","ror":"https://ror.org/04gzcxt97","country_code":"KR","type":"facility","lineage":["https://openalex.org/I2801339556","https://openalex.org/I4210144908","https://openalex.org/I4210161173","https://openalex.org/I4387152098"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Ju-Yeong Jung","raw_affiliation_strings":["Korea Railroad Research Institute, Uiwang, South Korea"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Korea Railroad Research Institute, Uiwang, South Korea","institution_ids":["https://openalex.org/I4210161173"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":{"value":1850,"currency":"USD","value_usd":1850},"apc_paid":{"value":1850,"currency":"USD","value_usd":1850},"fwci":5.5307,"has_fulltext":false,"cited_by_count":81,"citation_normalized_percentile":{"value":0.96107052,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":96,"max":100},"biblio":{"volume":"6","issue":null,"first_page":"60100","last_page":"60114"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11606","display_name":"Infrastructure Maintenance and Monitoring","score":1.0,"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":1.0,"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/T11850","display_name":"Concrete Corrosion and Durability","score":0.9919000267982483,"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/T10264","display_name":"Asphalt Pavement Performance Evaluation","score":0.9854999780654907,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/thresholding","display_name":"Thresholding","score":0.8724360466003418},{"id":"https://openalex.org/keywords/pixel","display_name":"Pixel","score":0.6883309483528137},{"id":"https://openalex.org/keywords/enhanced-data-rates-for-gsm-evolution","display_name":"Enhanced Data Rates for GSM Evolution","score":0.5758076906204224},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5426431894302368},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5292161107063293},{"id":"https://openalex.org/keywords/edge-detection","display_name":"Edge detection","score":0.4885348081588745},{"id":"https://openalex.org/keywords/noise","display_name":"Noise (video)","score":0.47426924109458923},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.4465329051017761},{"id":"https://openalex.org/keywords/consistency","display_name":"Consistency (knowledge bases)","score":0.41142377257347107},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.3241710662841797},{"id":"https://openalex.org/keywords/image-processing","display_name":"Image processing","score":0.26766419410705566}],"concepts":[{"id":"https://openalex.org/C191178318","wikidata":"https://www.wikidata.org/wiki/Q2256906","display_name":"Thresholding","level":3,"score":0.8724360466003418},{"id":"https://openalex.org/C160633673","wikidata":"https://www.wikidata.org/wiki/Q355198","display_name":"Pixel","level":2,"score":0.6883309483528137},{"id":"https://openalex.org/C162307627","wikidata":"https://www.wikidata.org/wiki/Q204833","display_name":"Enhanced Data Rates for GSM Evolution","level":2,"score":0.5758076906204224},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5426431894302368},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5292161107063293},{"id":"https://openalex.org/C193536780","wikidata":"https://www.wikidata.org/wiki/Q1513153","display_name":"Edge detection","level":4,"score":0.4885348081588745},{"id":"https://openalex.org/C99498987","wikidata":"https://www.wikidata.org/wiki/Q2210247","display_name":"Noise (video)","level":3,"score":0.47426924109458923},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.4465329051017761},{"id":"https://openalex.org/C2776436953","wikidata":"https://www.wikidata.org/wiki/Q5163215","display_name":"Consistency (knowledge bases)","level":2,"score":0.41142377257347107},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.3241710662841797},{"id":"https://openalex.org/C9417928","wikidata":"https://www.wikidata.org/wiki/Q1070689","display_name":"Image processing","level":3,"score":0.26766419410705566}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/access.2018.2875889","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2018.2875889","pdf_url":null,"source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},{"id":"pmh:oai:doaj.org/article:ad7dbbb9c4ae461892f4466639a571d8","is_oa":true,"landing_page_url":"https://doaj.org/article/ad7dbbb9c4ae461892f4466639a571d8","pdf_url":null,"source":{"id":"https://openalex.org/S4306401280","display_name":"DOAJ (DOAJ: Directory of Open Access Journals)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by-sa","license_id":"https://openalex.org/licenses/cc-by-sa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"IEEE Access, Vol 6, Pp 60100-60114 (2018)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.1109/access.2018.2875889","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2018.2875889","pdf_url":null,"source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},"sustainable_development_goals":[{"display_name":"Sustainable cities and communities","score":0.5899999737739563,"id":"https://metadata.un.org/sdg/11"}],"awards":[],"funders":[{"id":"https://openalex.org/F4320324625","display_name":"Korea Agency for Infrastructure Technology Advancement","ror":"https://ror.org/00rxf7n07"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":23,"referenced_works":["https://openalex.org/W1843688048","https://openalex.org/W1976217264","https://openalex.org/W1993097837","https://openalex.org/W2005029343","https://openalex.org/W2005603577","https://openalex.org/W2005817579","https://openalex.org/W2033318022","https://openalex.org/W2039183981","https://openalex.org/W2090409217","https://openalex.org/W2091149439","https://openalex.org/W2120356561","https://openalex.org/W2128880484","https://openalex.org/W2129534965","https://openalex.org/W2142159465","https://openalex.org/W2158265964","https://openalex.org/W2278098559","https://openalex.org/W2548545052","https://openalex.org/W2588612844","https://openalex.org/W2733621490","https://openalex.org/W2887124204","https://openalex.org/W4245145478","https://openalex.org/W6638837701","https://openalex.org/W6697685012"],"related_works":["https://openalex.org/W2050699221","https://openalex.org/W2155191322","https://openalex.org/W2067272521","https://openalex.org/W2148060698","https://openalex.org/W2315652488","https://openalex.org/W2028037572","https://openalex.org/W2039365229","https://openalex.org/W65623452","https://openalex.org/W2145843506","https://openalex.org/W4293054829"],"abstract_inverted_index":{"This":[0],"paper":[1],"describes":[2],"an":[3,26,35],"image-based":[4],"methodology":[5],"for":[6,105],"the":[7,59,82,88,98,102,111,145,159],"detection":[8,38],"of":[9,29,41,122,131],"structural":[10],"cracks":[11],"in":[12,153],"concrete.":[13],"The":[14,129,141],"conventional":[15,160],"approach":[16],"based":[17,125],"on":[18,126],"line":[19],"enhancement":[20],"filtering":[21],"has":[22,148],"problems":[23],"associated":[24],"with":[25,158],"inaccurate":[27],"extraction":[28],"edge":[30],"pixels.":[31,109],"We":[32],"therefore":[33],"propose":[34],"edge-based":[36],"crack":[37,44,50,62,72,123,155],"technique":[39,133,147],"consisting":[40],"five":[42],"steps:":[43],"width":[45,63,77,89,156],"transform,":[46,64],"aspect":[47,85],"ratio":[48,86],"filtering,":[49,87],"region":[51],"search,":[52],"hole":[53],"filling,":[54],"and":[55,69,75,106,138,151],"relative":[56,114],"thresholding.":[57,128],"In":[58,81,97,110],"first":[60],"step,":[61,84,113],"opposing":[65],"edges":[66],"are":[67],"identified":[68],"classified":[70],"as":[71],"candidate":[73],"pixels,":[74],"a":[76],"map":[78,90],"is":[79,92,118],"generated.":[80],"second":[83],"generated":[91],"used":[93],"to":[94],"remove":[95],"noise.":[96],"next":[99],"two":[100],"steps,":[101],"method":[103],"searches":[104],"restores":[107],"missing":[108],"last":[112],"thresholding,":[115],"residual":[116],"noise":[117],"removed":[119],"through":[120],"reclassification":[121],"regions":[124],"image-adaptive":[127],"performance":[130],"this":[132],"was":[134],"tested":[135],"using":[136],"synthetic":[137],"real":[139],"images.":[140],"results":[142],"show":[143],"that":[144],"proposed":[146],"greater":[149],"accuracy":[150],"consistency":[152],"measuring":[154],"compared":[157],"technique.":[161]},"counts_by_year":[{"year":2026,"cited_by_count":8},{"year":2025,"cited_by_count":7},{"year":2024,"cited_by_count":13},{"year":2023,"cited_by_count":11},{"year":2022,"cited_by_count":14},{"year":2021,"cited_by_count":12},{"year":2020,"cited_by_count":13},{"year":2019,"cited_by_count":3}],"updated_date":"2026-07-15T18:14:33.161393","created_date":"2025-10-10T00:00:00"}