{"id":"https://openalex.org/W2000594920","doi":"https://doi.org/10.1109/itsc.2012.6338693","title":"Tire classification from still images and video","display_name":"Tire classification from still images and video","publication_year":2012,"publication_date":"2012-09-01","ids":{"openalex":"https://openalex.org/W2000594920","doi":"https://doi.org/10.1109/itsc.2012.6338693","mag":"2000594920"},"language":"en","primary_location":{"id":"doi:10.1109/itsc.2012.6338693","is_oa":false,"landing_page_url":"https://doi.org/10.1109/itsc.2012.6338693","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2012 15th International IEEE Conference on Intelligent Transportation Systems","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/A5048671138","display_name":"Orhan Bulan","orcid":"https://orcid.org/0000-0002-7489-2641"},"institutions":[{"id":"https://openalex.org/I4210132870","display_name":"Xerox (United States)","ror":"https://ror.org/03jwzwq24","country_code":"US","type":"company","lineage":["https://openalex.org/I4210132870"]},{"id":"https://openalex.org/I97098773","display_name":"Webster University","ror":"https://ror.org/01x8j4206","country_code":"US","type":"education","lineage":["https://openalex.org/I97098773"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Orhan Bulan","raw_affiliation_strings":["Webster, NY, USA","Xerox Corporation, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Webster, NY, USA","institution_ids":["https://openalex.org/I97098773"]},{"raw_affiliation_string":"Xerox Corporation, USA","institution_ids":["https://openalex.org/I4210132870"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5107193055","display_name":"Edgar A. Bernal","orcid":"https://orcid.org/0000-0002-5732-065X"},"institutions":[{"id":"https://openalex.org/I4210132870","display_name":"Xerox (United States)","ror":"https://ror.org/03jwzwq24","country_code":"US","type":"company","lineage":["https://openalex.org/I4210132870"]},{"id":"https://openalex.org/I97098773","display_name":"Webster University","ror":"https://ror.org/01x8j4206","country_code":"US","type":"education","lineage":["https://openalex.org/I97098773"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Edgar A. Bernal","raw_affiliation_strings":["Webster, NY, USA","Xerox Corporation, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Webster, NY, USA","institution_ids":["https://openalex.org/I97098773"]},{"raw_affiliation_string":"Xerox Corporation, USA","institution_ids":["https://openalex.org/I4210132870"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5108513627","display_name":"Robert P. Loce","orcid":null},"institutions":[{"id":"https://openalex.org/I4210132870","display_name":"Xerox (United States)","ror":"https://ror.org/03jwzwq24","country_code":"US","type":"company","lineage":["https://openalex.org/I4210132870"]},{"id":"https://openalex.org/I97098773","display_name":"Webster University","ror":"https://ror.org/01x8j4206","country_code":"US","type":"education","lineage":["https://openalex.org/I97098773"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Robert P. Loce","raw_affiliation_strings":["Webster, NY, USA","Xerox Corporation, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Webster, NY, USA","institution_ids":["https://openalex.org/I97098773"]},{"raw_affiliation_string":"Xerox Corporation, USA","institution_ids":["https://openalex.org/I4210132870"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5102394066","display_name":"Wencheng Wu","orcid":null},"institutions":[{"id":"https://openalex.org/I4210132870","display_name":"Xerox (United States)","ror":"https://ror.org/03jwzwq24","country_code":"US","type":"company","lineage":["https://openalex.org/I4210132870"]},{"id":"https://openalex.org/I97098773","display_name":"Webster University","ror":"https://ror.org/01x8j4206","country_code":"US","type":"education","lineage":["https://openalex.org/I97098773"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Wencheng Wu","raw_affiliation_strings":["Webster, NY, USA","Xerox Corporation, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Webster, NY, USA","institution_ids":["https://openalex.org/I97098773"]},{"raw_affiliation_string":"Xerox Corporation, USA","institution_ids":["https://openalex.org/I4210132870"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.4512,"has_fulltext":false,"cited_by_count":8,"citation_normalized_percentile":{"value":0.58086106,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":97},"biblio":{"volume":null,"issue":null,"first_page":"485","last_page":"490"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12549","display_name":"Image and Object Detection Techniques","score":0.9671000242233276,"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/T12549","display_name":"Image and Object Detection Techniques","score":0.9671000242233276,"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/T12111","display_name":"Industrial Vision Systems and Defect Detection","score":0.9609000086784363,"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/T11164","display_name":"Remote Sensing and LiDAR Applications","score":0.9598000049591064,"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/support-vector-machine","display_name":"Support vector machine","score":0.7727119326591492},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.7515195608139038},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.7495954036712646},{"id":"https://openalex.org/keywords/robustness","display_name":"Robustness (evolution)","score":0.6847391128540039},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.6626877188682556},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5861997008323669},{"id":"https://openalex.org/keywords/contextual-image-classification","display_name":"Contextual image classification","score":0.5840063691139221},{"id":"https://openalex.org/keywords/principal-component-analysis","display_name":"Principal component analysis","score":0.5454930663108826},{"id":"https://openalex.org/keywords/tread","display_name":"Tread","score":0.5352829694747925},{"id":"https://openalex.org/keywords/classifier","display_name":"Classifier (UML)","score":0.5202273726463318},{"id":"https://openalex.org/keywords/binary-classification","display_name":"Binary classification","score":0.4204733967781067},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.3968280553817749},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.1733720898628235},{"id":"https://openalex.org/keywords/natural-rubber","display_name":"Natural rubber","score":0.1595112383365631}],"concepts":[{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.7727119326591492},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7515195608139038},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.7495954036712646},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.6847391128540039},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.6626877188682556},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5861997008323669},{"id":"https://openalex.org/C75294576","wikidata":"https://www.wikidata.org/wiki/Q5165192","display_name":"Contextual image classification","level":3,"score":0.5840063691139221},{"id":"https://openalex.org/C27438332","wikidata":"https://www.wikidata.org/wiki/Q2873","display_name":"Principal component analysis","level":2,"score":0.5454930663108826},{"id":"https://openalex.org/C155296804","wikidata":"https://www.wikidata.org/wiki/Q30329684","display_name":"Tread","level":3,"score":0.5352829694747925},{"id":"https://openalex.org/C95623464","wikidata":"https://www.wikidata.org/wiki/Q1096149","display_name":"Classifier (UML)","level":2,"score":0.5202273726463318},{"id":"https://openalex.org/C66905080","wikidata":"https://www.wikidata.org/wiki/Q17005494","display_name":"Binary classification","level":3,"score":0.4204733967781067},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.3968280553817749},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.1733720898628235},{"id":"https://openalex.org/C176933379","wikidata":"https://www.wikidata.org/wiki/Q131877","display_name":"Natural rubber","level":2,"score":0.1595112383365631},{"id":"https://openalex.org/C55493867","wikidata":"https://www.wikidata.org/wiki/Q7094","display_name":"Biochemistry","level":1,"score":0.0},{"id":"https://openalex.org/C104317684","wikidata":"https://www.wikidata.org/wiki/Q7187","display_name":"Gene","level":2,"score":0.0},{"id":"https://openalex.org/C178790620","wikidata":"https://www.wikidata.org/wiki/Q11351","display_name":"Organic chemistry","level":1,"score":0.0},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/itsc.2012.6338693","is_oa":false,"landing_page_url":"https://doi.org/10.1109/itsc.2012.6338693","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2012 15th International IEEE Conference on Intelligent Transportation Systems","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/16","display_name":"Peace, Justice and strong institutions","score":0.7799999713897705}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":6,"referenced_works":["https://openalex.org/W2024534252","https://openalex.org/W2067042811","https://openalex.org/W2098693229","https://openalex.org/W2102544846","https://openalex.org/W2145023731","https://openalex.org/W4234750346"],"related_works":["https://openalex.org/W2380565719","https://openalex.org/W2005234362","https://openalex.org/W1997235926","https://openalex.org/W4382934300","https://openalex.org/W2121061354","https://openalex.org/W4285388059","https://openalex.org/W2910954186","https://openalex.org/W4205999209","https://openalex.org/W2444525338","https://openalex.org/W4288570796"],"abstract_inverted_index":{"The":[0,109],"use":[1],"of":[2,5,22,57,76,80,99,119,151,156],"different":[3],"types":[4],"tires":[6,43,49],"(e.g.,":[7],"all-season,":[8],"snow,":[9,45],"studded,":[10],"summer)":[11],"is":[12,84,116],"regulated":[13],"by":[14,103],"law":[15],"in":[16,28,139],"several":[17],"states":[18],"and":[19,47,92,141],"countries.":[20],"Violation":[21],"tire":[23,82,93,120,158],"usage":[24],"laws":[25],"typically":[26],"results":[27,163],"substantial":[29],"fines":[30],"for":[31],"infringers.":[32],"In":[33,132],"this":[34],"paper,":[35],"we":[36],"propose":[37],"an":[38],"automated":[39],"method":[40,61,168],"to":[41,134,137],"classify":[42],"into":[44],"all-season":[46],"summer":[48],"from":[50,54,73,127,147],"still":[51],"images":[52,83,121],"or":[53],"a":[55,64,74,85,123],"sequence":[56],"video":[58],"frames.":[59],"Our":[60,161],"first":[62],"trains":[63],"Support":[65],"Vector":[66],"Machine":[67],"(SVM)":[68],"classifier":[69],"on":[70,96],"features":[71,102,144],"extracted":[72,101,146],"set":[75],"training":[77],"images.":[78],"Classification":[79],"test":[81],"two-stage":[86],"process":[87],"that":[88,165],"entails":[89],"feature":[90,113],"extraction":[91,114],"classification":[94,171],"based":[95],"the":[97,100,104,112,117,143,148,152,157,166],"processing":[98],"previously":[105],"trained":[106],"SVM":[107],"classifier.":[108],"principle":[110],"underlying":[111],"stage":[115],"representation":[118,150],"via":[122],"low-dimensional":[124],"approximation":[125],"obtained":[126],"Principal":[128],"Component":[129],"Analysis":[130],"(PCA).":[131],"order":[133],"improve":[135],"robustness":[136],"changes":[138],"illumination":[140],"perspective,":[142],"are":[145],"frequency":[149],"binary":[153],"edge":[154],"map":[155],"tread":[159],"image.":[160],"experimental":[162],"show":[164],"proposed":[167],"achieves":[169],"high":[170],"accuracy.":[172]},"counts_by_year":[{"year":2024,"cited_by_count":3},{"year":2023,"cited_by_count":1},{"year":2021,"cited_by_count":2},{"year":2014,"cited_by_count":1},{"year":2013,"cited_by_count":1}],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2025-10-10T00:00:00"}