{"id":"https://openalex.org/W2067244803","doi":"https://doi.org/10.1109/icics.2013.6782965","title":"Statistical modeling of the Gabor filter magnitude using Gamma distribution for effectively vehicle verification","display_name":"Statistical modeling of the Gabor filter magnitude using Gamma distribution for effectively vehicle verification","publication_year":2013,"publication_date":"2013-12-01","ids":{"openalex":"https://openalex.org/W2067244803","doi":"https://doi.org/10.1109/icics.2013.6782965","mag":"2067244803"},"language":"en","primary_location":{"id":"doi:10.1109/icics.2013.6782965","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icics.2013.6782965","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2013 9th International Conference on Information, Communications & Signal Processing","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/A5089868194","display_name":"Jing-Ming Guo","orcid":"https://orcid.org/0000-0002-8041-6326"},"institutions":[{"id":"https://openalex.org/I154864474","display_name":"National Taiwan University of Science and Technology","ror":"https://ror.org/00q09pe49","country_code":"TW","type":"education","lineage":["https://openalex.org/I154864474"]}],"countries":["TW"],"is_corresponding":true,"raw_author_name":"Jing-Ming Guo","raw_affiliation_strings":["Department of Electrical Engineering, National Taiwan University of Science and Technology, Taipei, Taiwan","Dept. of Electr. Eng., Nat. Taiwan Univ. of Science & Technol., Taipei, Taiwan"],"affiliations":[{"raw_affiliation_string":"Department of Electrical Engineering, National Taiwan University of Science and Technology, Taipei, Taiwan","institution_ids":["https://openalex.org/I154864474"]},{"raw_affiliation_string":"Dept. of Electr. Eng., Nat. Taiwan Univ. of Science & Technol., Taipei, Taiwan","institution_ids":["https://openalex.org/I154864474"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5004946227","display_name":"Heri Prasetyo","orcid":"https://orcid.org/0000-0002-1257-4832"},"institutions":[{"id":"https://openalex.org/I154864474","display_name":"National Taiwan University of Science and Technology","ror":"https://ror.org/00q09pe49","country_code":"TW","type":"education","lineage":["https://openalex.org/I154864474"]}],"countries":["TW"],"is_corresponding":false,"raw_author_name":"Heri Prasetyo","raw_affiliation_strings":["National Taiwan University of Science and Technology, Taipei, TW","Dept. of Electr. Eng., Nat. Taiwan Univ. of Science & Technol., Taipei, Taiwan"],"affiliations":[{"raw_affiliation_string":"National Taiwan University of Science and Technology, Taipei, TW","institution_ids":["https://openalex.org/I154864474"]},{"raw_affiliation_string":"Dept. of Electr. Eng., Nat. Taiwan Univ. of Science & Technol., Taipei, Taiwan","institution_ids":["https://openalex.org/I154864474"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5089868194"],"corresponding_institution_ids":["https://openalex.org/I154864474"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.13193184,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"18","issue":null,"first_page":"1","last_page":"4"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12549","display_name":"Image and Object Detection Techniques","score":0.9965000152587891,"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":0.9965000152587891,"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/T10824","display_name":"Image Retrieval and Classification Techniques","score":0.9962999820709229,"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/T12357","display_name":"Digital Media Forensic Detection","score":0.9959999918937683,"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/gabor-filter","display_name":"Gabor filter","score":0.7686254978179932},{"id":"https://openalex.org/keywords/skewness","display_name":"Skewness","score":0.7459601163864136},{"id":"https://openalex.org/keywords/standard-deviation","display_name":"Standard deviation","score":0.6714766621589661},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.6623567938804626},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6582349538803101},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.5616722106933594},{"id":"https://openalex.org/keywords/curse-of-dimensionality","display_name":"Curse of dimensionality","score":0.48209527134895325},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.45519718527793884},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.45495739579200745},{"id":"https://openalex.org/keywords/gaussian","display_name":"Gaussian","score":0.44067493081092834},{"id":"https://openalex.org/keywords/filter","display_name":"Filter (signal processing)","score":0.43150794506073},{"id":"https://openalex.org/keywords/gamma-distribution","display_name":"Gamma distribution","score":0.41186654567718506},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.40109342336654663},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.3455287218093872},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.288343220949173},{"id":"https://openalex.org/keywords/physics","display_name":"Physics","score":0.07489880919456482}],"concepts":[{"id":"https://openalex.org/C2779883129","wikidata":"https://www.wikidata.org/wiki/Q2447890","display_name":"Gabor filter","level":3,"score":0.7686254978179932},{"id":"https://openalex.org/C122342681","wikidata":"https://www.wikidata.org/wiki/Q330828","display_name":"Skewness","level":2,"score":0.7459601163864136},{"id":"https://openalex.org/C22679943","wikidata":"https://www.wikidata.org/wiki/Q159375","display_name":"Standard deviation","level":2,"score":0.6714766621589661},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.6623567938804626},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6582349538803101},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.5616722106933594},{"id":"https://openalex.org/C111030470","wikidata":"https://www.wikidata.org/wiki/Q1430460","display_name":"Curse of dimensionality","level":2,"score":0.48209527134895325},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.45519718527793884},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.45495739579200745},{"id":"https://openalex.org/C163716315","wikidata":"https://www.wikidata.org/wiki/Q901177","display_name":"Gaussian","level":2,"score":0.44067493081092834},{"id":"https://openalex.org/C106131492","wikidata":"https://www.wikidata.org/wiki/Q3072260","display_name":"Filter (signal processing)","level":2,"score":0.43150794506073},{"id":"https://openalex.org/C149717495","wikidata":"https://www.wikidata.org/wiki/Q117806","display_name":"Gamma distribution","level":2,"score":0.41186654567718506},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.40109342336654663},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.3455287218093872},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.288343220949173},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.07489880919456482},{"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/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icics.2013.6782965","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icics.2013.6782965","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2013 9th International Conference on Information, Communications & Signal Processing","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":9,"referenced_works":["https://openalex.org/W2027628481","https://openalex.org/W2059536461","https://openalex.org/W2114701495","https://openalex.org/W2138584058","https://openalex.org/W2146769544","https://openalex.org/W2154271851","https://openalex.org/W2158182800","https://openalex.org/W3099006300","https://openalex.org/W6683522609"],"related_works":["https://openalex.org/W2189529952","https://openalex.org/W3122032734","https://openalex.org/W28389960","https://openalex.org/W3144675622","https://openalex.org/W3124374489","https://openalex.org/W2153442034","https://openalex.org/W2163571608","https://openalex.org/W2084723156","https://openalex.org/W1993982689","https://openalex.org/W2771883571"],"abstract_inverted_index":{"Vehicle":[0],"verification":[1,144],"based":[2],"on":[3,108],"still":[4],"image":[5,15,48],"feature":[6,86,105],"can":[7],"be":[8],"considered":[9],"as":[10,41],"supervised":[11],"classification":[12],"problem.":[13],"An":[14],"descriptor":[16,49,87,130],"is":[17,39,50,77,88,153],"directly":[18],"derived":[19,131],"from":[20,52,132],"the":[21,32,35,42,47,60,74,81,85,111,114,122,133,138,150,156],"Gabor":[22,36,61,98,115],"filtered":[23,37],"output":[24,38,99],"statistics":[25],"of":[26,34,59,97,113,137],"a":[27,127],"given":[28],"image.":[29],"In":[30],"general,":[31],"magnitude":[33,63,112],"modeled":[40],"Gaussian":[43],"distribution.":[44,124],"So":[45],"that":[46,73,149],"composed":[51],"mean,":[53],"standard":[54,95],"deviation,":[55],"and":[56,94],"skewness":[57,75],"value":[58],"filter":[62,116],"[5,":[64],"6,":[65],"8].":[66],"However,":[67],"Arrospide":[68],"et.":[69],"al.":[70],"[9]":[71],"argued":[72],"parameter":[76],"not":[78],"meaningful":[79],"for":[80,141],"class":[82],"separation.":[83],"Then,":[84],"well":[89],"defined":[90],"only":[91],"using":[92],"mean":[93],"deviation":[96],"distribution":[100,140],"which":[101],"leads":[102],"to":[103,120,155],"lower":[104],"dimensionality.":[106],"Based":[107],"our":[109],"observation,":[110],"has":[117],"strong":[118],"tendency":[119],"follow":[121],"Gamma":[123,139],"We":[125],"propose":[126],"new":[128],"texture":[129],"maximum":[134],"likelihood":[135],"estimation":[136],"effectively":[142],"vehicle":[143],"task.":[145],"Experimental":[146],"result":[147],"shows":[148],"proposed":[151],"method":[152],"superior":[154],"former":[157],"approach":[158],"under":[159],"several":[160],"classifier":[161],"techniques.":[162]},"counts_by_year":[],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}