{"id":"https://openalex.org/W2091401910","doi":"https://doi.org/10.1109/icmlc.2014.7009668","title":"A real-time algorithm for aluminum surface defect extraction on non-uniform image from CCD camera","display_name":"A real-time algorithm for aluminum surface defect extraction on non-uniform image from CCD camera","publication_year":2014,"publication_date":"2014-07-01","ids":{"openalex":"https://openalex.org/W2091401910","doi":"https://doi.org/10.1109/icmlc.2014.7009668","mag":"2091401910"},"language":"en","primary_location":{"id":"doi:10.1109/icmlc.2014.7009668","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icmlc.2014.7009668","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2014 International Conference on Machine Learning and Cybernetics","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/A5065795063","display_name":"Xiu-Qin Huang","orcid":"https://orcid.org/0009-0001-3298-8602"},"institutions":[{"id":"https://openalex.org/I4210109250","display_name":"Suzhou Nonferrous Metals Research Institute","ror":"https://ror.org/01qr4nw81","country_code":"CN","type":"facility","lineage":["https://openalex.org/I4210109250"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Xiu-Qin Huang","raw_affiliation_strings":["Suzhou Non-ferrous Metals Research Institute, Suzhou, Jiangsu, China"],"affiliations":[{"raw_affiliation_string":"Suzhou Non-ferrous Metals Research Institute, Suzhou, Jiangsu, China","institution_ids":["https://openalex.org/I4210109250"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100296539","display_name":"Xin-Bin Luo","orcid":null},"institutions":[{"id":"https://openalex.org/I4210109250","display_name":"Suzhou Nonferrous Metals Research Institute","ror":"https://ror.org/01qr4nw81","country_code":"CN","type":"facility","lineage":["https://openalex.org/I4210109250"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xin-Bin Luo","raw_affiliation_strings":["School of Aeronautics and Astronautics, Shanghai Jiaotong University, China","Suzhou Non-ferrous Metals Research Institute, Suzhou, Jiangsu, China"],"affiliations":[{"raw_affiliation_string":"School of Aeronautics and Astronautics, Shanghai Jiaotong University, China","institution_ids":[]},{"raw_affiliation_string":"Suzhou Non-ferrous Metals Research Institute, Suzhou, Jiangsu, China","institution_ids":["https://openalex.org/I4210109250"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5065795063"],"corresponding_institution_ids":["https://openalex.org/I4210109250"],"apc_list":null,"apc_paid":null,"fwci":1.2315,"has_fulltext":false,"cited_by_count":14,"citation_normalized_percentile":{"value":0.83783581,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":98},"biblio":{"volume":"12","issue":null,"first_page":"556","last_page":"561"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12111","display_name":"Industrial Vision Systems and Defect Detection","score":1.0,"subfield":{"id":"https://openalex.org/subfields/2209","display_name":"Industrial and Manufacturing 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/T12111","display_name":"Industrial Vision Systems and Defect Detection","score":1.0,"subfield":{"id":"https://openalex.org/subfields/2209","display_name":"Industrial and Manufacturing 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/T13114","display_name":"Image Processing Techniques and Applications","score":0.9993000030517578,"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/T12549","display_name":"Image and Object Detection Techniques","score":0.9991999864578247,"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/prewitt-operator","display_name":"Prewitt operator","score":0.8523956537246704},{"id":"https://openalex.org/keywords/smoothing","display_name":"Smoothing","score":0.6306649446487427},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5957261323928833},{"id":"https://openalex.org/keywords/edge-detection","display_name":"Edge detection","score":0.5908608436584473},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5866440534591675},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.5768534541130066},{"id":"https://openalex.org/keywords/image-segmentation","display_name":"Image segmentation","score":0.4831656813621521},{"id":"https://openalex.org/keywords/gaussian-blur","display_name":"Gaussian blur","score":0.47076964378356934},{"id":"https://openalex.org/keywords/enhanced-data-rates-for-gsm-evolution","display_name":"Enhanced Data Rates for GSM Evolution","score":0.4588488042354584},{"id":"https://openalex.org/keywords/gaussian","display_name":"Gaussian","score":0.45411136746406555},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.40864476561546326},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.3894474506378174},{"id":"https://openalex.org/keywords/image-processing","display_name":"Image processing","score":0.32969558238983154},{"id":"https://openalex.org/keywords/image-restoration","display_name":"Image restoration","score":0.14643746614456177}],"concepts":[{"id":"https://openalex.org/C155012704","wikidata":"https://www.wikidata.org/wiki/Q451898","display_name":"Prewitt operator","level":5,"score":0.8523956537246704},{"id":"https://openalex.org/C3770464","wikidata":"https://www.wikidata.org/wiki/Q775963","display_name":"Smoothing","level":2,"score":0.6306649446487427},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5957261323928833},{"id":"https://openalex.org/C193536780","wikidata":"https://www.wikidata.org/wiki/Q1513153","display_name":"Edge detection","level":4,"score":0.5908608436584473},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5866440534591675},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.5768534541130066},{"id":"https://openalex.org/C124504099","wikidata":"https://www.wikidata.org/wiki/Q56933","display_name":"Image segmentation","level":3,"score":0.4831656813621521},{"id":"https://openalex.org/C104317376","wikidata":"https://www.wikidata.org/wiki/Q1894545","display_name":"Gaussian blur","level":5,"score":0.47076964378356934},{"id":"https://openalex.org/C162307627","wikidata":"https://www.wikidata.org/wiki/Q204833","display_name":"Enhanced Data Rates for GSM Evolution","level":2,"score":0.4588488042354584},{"id":"https://openalex.org/C163716315","wikidata":"https://www.wikidata.org/wiki/Q901177","display_name":"Gaussian","level":2,"score":0.45411136746406555},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.40864476561546326},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.3894474506378174},{"id":"https://openalex.org/C9417928","wikidata":"https://www.wikidata.org/wiki/Q1070689","display_name":"Image processing","level":3,"score":0.32969558238983154},{"id":"https://openalex.org/C106430172","wikidata":"https://www.wikidata.org/wiki/Q6002272","display_name":"Image restoration","level":4,"score":0.14643746614456177},{"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/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/icmlc.2014.7009668","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icmlc.2014.7009668","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2014 International Conference on Machine Learning and Cybernetics","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":15,"referenced_works":["https://openalex.org/W1577671906","https://openalex.org/W1970614856","https://openalex.org/W1987087490","https://openalex.org/W2022153489","https://openalex.org/W2051323180","https://openalex.org/W2083970667","https://openalex.org/W2099111195","https://openalex.org/W2104696435","https://openalex.org/W2111007172","https://openalex.org/W2114760733","https://openalex.org/W2118348777","https://openalex.org/W2139176774","https://openalex.org/W4240744150","https://openalex.org/W6655800812","https://openalex.org/W6680405853"],"related_works":["https://openalex.org/W2385342205","https://openalex.org/W2545393398","https://openalex.org/W2348584852","https://openalex.org/W2378692644","https://openalex.org/W2318773630","https://openalex.org/W1495469551","https://openalex.org/W2558559991","https://openalex.org/W3134757346","https://openalex.org/W2379894902","https://openalex.org/W2063769574"],"abstract_inverted_index":{"A":[0],"novel":[1],"real-time":[2,105],"defect":[3,59],"extraction":[4,60],"framework":[5,79],"is":[6,20,32,43,62,70,80],"proposed":[7,78,102],"for":[8],"handling":[9],"non-uniform":[10],"images":[11,90],"in":[12,114],"high-speed":[13],"aluminum":[14,87],"strip":[15,88],"surface":[16,89],"inspection.":[17],"The":[18,57,67,77,96],"image":[19,35,61],"first":[21],"preprocessed":[22],"by":[23],"Gaussian":[24],"smoothing":[25],"operator":[26],"and":[27,52,73,108],"Prewitt":[28],"edge":[29,55],"detection,":[30],"which":[31],"robust":[33,74],"to":[34,45,75],"non-uniformity.":[36,76],"Afterwards,":[37],"a":[38,83],"fast":[39],"adaptive":[40],"segmentation":[41],"algorithm":[42],"applied":[44],"further":[46],"remove":[47],"the":[48,54,93,101,111],"effect":[49],"of":[50,86],"non-uniformity":[51],"enhance":[53],"detection.":[56],"final":[58],"achieved":[63],"through":[64],"morphological":[65],"operations.":[66],"resultant":[68],"method":[69,103],"computationally":[71],"efficient":[72],"evaluated":[81],"on":[82],"large":[84],"dataset":[85],"obtained":[91],"from":[92],"product":[94],"line.":[95],"experimental":[97],"results":[98],"show":[99],"that":[100],"achieves":[104],"defects":[106],"extraction,":[107],"it":[109],"outperforms":[110],"previous":[112],"methods":[113],"accuracy.":[115]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":2},{"year":2023,"cited_by_count":5},{"year":2020,"cited_by_count":2},{"year":2019,"cited_by_count":1},{"year":2018,"cited_by_count":1},{"year":2017,"cited_by_count":1},{"year":2015,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
