{"id":"https://openalex.org/W2006069468","doi":"https://doi.org/10.1109/tcyb.2014.2346793","title":"High-Order Statistics of Weber Local Descriptors for Image Representation","display_name":"High-Order Statistics of Weber Local Descriptors for Image Representation","publication_year":2014,"publication_date":"2014-08-26","ids":{"openalex":"https://openalex.org/W2006069468","doi":"https://doi.org/10.1109/tcyb.2014.2346793","mag":"2006069468","pmid":"https://pubmed.ncbi.nlm.nih.gov/25167565"},"language":"en","primary_location":{"id":"doi:10.1109/tcyb.2014.2346793","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tcyb.2014.2346793","pdf_url":null,"source":{"id":"https://openalex.org/S4210191041","display_name":"IEEE Transactions on Cybernetics","issn_l":"2168-2267","issn":["2168-2267","2168-2275"],"is_oa":false,"is_in_doaj":false,"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 Transactions on Cybernetics","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","pubmed"],"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/A5086851360","display_name":"Xian\u2010Hua Han","orcid":"https://orcid.org/0000-0002-5003-3180"},"institutions":[{"id":"https://openalex.org/I135768898","display_name":"Ritsumeikan University","ror":"https://ror.org/0197nmd03","country_code":"JP","type":"education","lineage":["https://openalex.org/I135768898","https://openalex.org/I4390039241"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Xian-Hua Han","raw_affiliation_strings":["College of Information Science and Engineering, Ritsumeikan University, Kasatsu-shi, Japan","College of Information Science and Engineering, Ritsumeikan University, Kasatsu-shi, Japan#TAB#"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"College of Information Science and Engineering, Ritsumeikan University, Kasatsu-shi, Japan","institution_ids":["https://openalex.org/I135768898"]},{"raw_affiliation_string":"College of Information Science and Engineering, Ritsumeikan University, Kasatsu-shi, Japan#TAB#","institution_ids":["https://openalex.org/I135768898"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5044216245","display_name":"Yen\u2010Wei Chen","orcid":"https://orcid.org/0000-0002-5952-0188"},"institutions":[{"id":"https://openalex.org/I135768898","display_name":"Ritsumeikan University","ror":"https://ror.org/0197nmd03","country_code":"JP","type":"education","lineage":["https://openalex.org/I135768898","https://openalex.org/I4390039241"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Yen-Wei Chen","raw_affiliation_strings":["College of Information Science and Engineering, Ritsumeikan University, Kasatsu-shi, Japan","College of Information Science and Engineering, Ritsumeikan University, Kasatsu-shi, Japan#TAB#"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"College of Information Science and Engineering, Ritsumeikan University, Kasatsu-shi, Japan","institution_ids":["https://openalex.org/I135768898"]},{"raw_affiliation_string":"College of Information Science and Engineering, Ritsumeikan University, Kasatsu-shi, Japan#TAB#","institution_ids":["https://openalex.org/I135768898"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5087493208","display_name":"Gang Xu","orcid":"https://orcid.org/0000-0001-9875-051X"},"institutions":[{"id":"https://openalex.org/I135768898","display_name":"Ritsumeikan University","ror":"https://ror.org/0197nmd03","country_code":"JP","type":"education","lineage":["https://openalex.org/I135768898","https://openalex.org/I4390039241"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Gang Xu","raw_affiliation_strings":["College of Information Science and Engineering, Ritsumeikan University, Kasatsu-shi, Japan","College of Information Science and Engineering, Ritsumeikan University, Kasatsu-shi, Japan#TAB#"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"College of Information Science and Engineering, Ritsumeikan University, Kasatsu-shi, Japan","institution_ids":["https://openalex.org/I135768898"]},{"raw_affiliation_string":"College of Information Science and Engineering, Ritsumeikan University, Kasatsu-shi, Japan#TAB#","institution_ids":["https://openalex.org/I135768898"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I135768898"],"apc_list":null,"apc_paid":null,"fwci":2.9113,"has_fulltext":false,"cited_by_count":33,"citation_normalized_percentile":{"value":0.92792445,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":89,"max":99},"biblio":{"volume":"45","issue":"6","first_page":"1180","last_page":"1193"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10627","display_name":"Advanced Image and Video Retrieval Techniques","score":0.9997000098228455,"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/T10627","display_name":"Advanced Image and Video Retrieval Techniques","score":0.9997000098228455,"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":0.9987000226974487,"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/T10057","display_name":"Face and Expression Recognition","score":0.9868000149726868,"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/artificial-intelligence","display_name":"Artificial intelligence","score":0.7425693869590759},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.6983308792114258},{"id":"https://openalex.org/keywords/discriminant","display_name":"Discriminant","score":0.5450409650802612},{"id":"https://openalex.org/keywords/linear-discriminant-analysis","display_name":"Linear discriminant analysis","score":0.5350023508071899},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.5099903345108032},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.4904927611351013},{"id":"https://openalex.org/keywords/generative-model","display_name":"Generative model","score":0.48391610383987427},{"id":"https://openalex.org/keywords/parametric-statistics","display_name":"Parametric statistics","score":0.4647983908653259},{"id":"https://openalex.org/keywords/generative-grammar","display_name":"Generative grammar","score":0.24512824416160583},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.16884958744049072}],"concepts":[{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7425693869590759},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.6983308792114258},{"id":"https://openalex.org/C78397625","wikidata":"https://www.wikidata.org/wiki/Q192487","display_name":"Discriminant","level":2,"score":0.5450409650802612},{"id":"https://openalex.org/C69738355","wikidata":"https://www.wikidata.org/wiki/Q1228929","display_name":"Linear discriminant analysis","level":2,"score":0.5350023508071899},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.5099903345108032},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.4904927611351013},{"id":"https://openalex.org/C167966045","wikidata":"https://www.wikidata.org/wiki/Q5532625","display_name":"Generative model","level":3,"score":0.48391610383987427},{"id":"https://openalex.org/C117251300","wikidata":"https://www.wikidata.org/wiki/Q1849855","display_name":"Parametric statistics","level":2,"score":0.4647983908653259},{"id":"https://openalex.org/C39890363","wikidata":"https://www.wikidata.org/wiki/Q36108","display_name":"Generative grammar","level":2,"score":0.24512824416160583},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.16884958744049072}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/tcyb.2014.2346793","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tcyb.2014.2346793","pdf_url":null,"source":{"id":"https://openalex.org/S4210191041","display_name":"IEEE Transactions on Cybernetics","issn_l":"2168-2267","issn":["2168-2267","2168-2275"],"is_oa":false,"is_in_doaj":false,"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 Transactions on Cybernetics","raw_type":"journal-article"},{"id":"pmid:25167565","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/25167565","pdf_url":null,"source":{"id":"https://openalex.org/S4306525036","display_name":"PubMed","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1299303238","host_organization_name":"National Institutes of Health","host_organization_lineage":["https://openalex.org/I1299303238"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE transactions on cybernetics","raw_type":null}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Reduced inequalities","score":0.6499999761581421,"id":"https://metadata.un.org/sdg/10"}],"awards":[{"id":"https://openalex.org/G6463612153","display_name":"Study on Image Representation Learning and Understanding based on Human's Perception Principle and Deep Statistical Analysis","funder_award_id":"15K00253","funder_id":"https://openalex.org/F4320334764","funder_display_name":"Japan Society for the Promotion of Science"}],"funders":[{"id":"https://openalex.org/F4320334764","display_name":"Japan Society for the Promotion of Science","ror":"https://ror.org/00hhkn466"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":60,"referenced_works":["https://openalex.org/W1528620860","https://openalex.org/W1548783750","https://openalex.org/W1556531089","https://openalex.org/W1563088657","https://openalex.org/W1573082642","https://openalex.org/W1601795611","https://openalex.org/W1619841130","https://openalex.org/W1663973292","https://openalex.org/W1971877752","https://openalex.org/W2027922120","https://openalex.org/W2041272430","https://openalex.org/W2049633694","https://openalex.org/W2050384470","https://openalex.org/W2055527244","https://openalex.org/W2067848192","https://openalex.org/W2088866137","https://openalex.org/W2089802788","https://openalex.org/W2096761622","https://openalex.org/W2097018403","https://openalex.org/W2098305432","https://openalex.org/W2108082645","https://openalex.org/W2111308925","https://openalex.org/W2111815479","https://openalex.org/W2112020727","https://openalex.org/W2116427319","https://openalex.org/W2123745357","https://openalex.org/W2124386111","https://openalex.org/W2126833203","https://openalex.org/W2128017662","https://openalex.org/W2129976136","https://openalex.org/W2130258210","https://openalex.org/W2131846894","https://openalex.org/W2134199473","https://openalex.org/W2145072179","https://openalex.org/W2148809531","https://openalex.org/W2149132745","https://openalex.org/W2151103935","https://openalex.org/W2153786187","https://openalex.org/W2161969291","https://openalex.org/W2162915993","https://openalex.org/W2163352848","https://openalex.org/W2166473218","https://openalex.org/W2171253919","https://openalex.org/W2340980467","https://openalex.org/W2395532456","https://openalex.org/W2543932557","https://openalex.org/W2548197316","https://openalex.org/W4285719527","https://openalex.org/W6633472159","https://openalex.org/W6634556549","https://openalex.org/W6636583343","https://openalex.org/W6664275923","https://openalex.org/W6667131817","https://openalex.org/W6674642818","https://openalex.org/W6676770471","https://openalex.org/W6678853083","https://openalex.org/W6681554747","https://openalex.org/W6684116732","https://openalex.org/W6685330537","https://openalex.org/W6704299076"],"related_works":["https://openalex.org/W2350751952","https://openalex.org/W1999647744","https://openalex.org/W2362114017","https://openalex.org/W3147024994","https://openalex.org/W2063246903","https://openalex.org/W2374055396","https://openalex.org/W1978302214","https://openalex.org/W2021817983","https://openalex.org/W2156856390","https://openalex.org/W3008559849"],"abstract_inverted_index":{"Highly":[0],"discriminant":[1,164],"visual":[2],"features":[3,23],"play":[4],"a":[5,18,28,50,84,94,113],"key":[6],"role":[7],"in":[8,80,99],"different":[9,181],"image":[10,133,182],"classification":[11,183],"applications.":[12],"This":[13],"study":[14],"aims":[15],"to":[16,88,111,117,128,162,170],"realize":[17],"method":[19],"for":[20,48,132,153,166],"extracting":[21],"highly-discriminant":[22],"from":[24],"images":[25,79,188],"by":[26,33],"exploring":[27],"robust":[29],"local":[30,38,95,105,121],"descriptor":[31,39,106],"inspired":[32],"Weber's":[34,89],"law.":[35],"The":[36,135],"investigated":[37],"is":[40],"based":[41],"on":[42,55,64],"the":[43,56,60,65,69,75,100,119,125,129,141,151,156,172,175,203],"fact":[44],"that":[45,196],"human":[46],"perception":[47],"distinguishing":[49],"pattern":[51,192],"depends":[52],"not":[53],"only":[54],"absolute":[57],"intensity":[58],"of":[59,68,174],"stimulus":[61,77],"but":[62],"also":[63],"relative":[66],"variance":[67],"stimulus.":[70],"Therefore,":[71],"we":[72,109,178],"firstly":[73],"transform":[74],"original":[76],"(the":[78],"our":[81,197],"study)":[82],"into":[83],"differential":[85],"excitation-domain":[86],"according":[87],"law,":[90],"and":[91,123,148,189],"then":[92,149],"explore":[93],"patch,":[96],"called":[97],"micro-Texton,":[98],"transformed":[101],"domain":[102],"as":[103],"Weber":[104,120],"(WLD).":[107],"Furthermore,":[108],"propose":[110],"employ":[112],"parametric":[114],"probability":[115,146],"process":[116],"model":[118,130],"descriptors,":[122],"extract":[124],"higher-order":[126],"statistics":[127],"parameters":[131,152],"representation.":[134],"proposed":[136,176,198],"strategy":[137,199],"can":[138],"adaptively":[139],"characterize":[140],"WLD":[142],"space":[143],"using":[144],"generative":[145],"model,":[147],"learn":[150],"better":[154],"fitting":[155],"training":[157],"space,":[158],"which":[159,194],"would":[160],"lead":[161],"more":[163],"representation":[165],"images.":[167],"In":[168],"order":[169],"validate":[171],"efficiency":[173],"strategy,":[177],"apply":[179],"three":[180],"applications":[184],"including":[185],"texture,":[186],"food":[187],"HEp-2":[190],"cell":[191],"recognition,":[193],"validates":[195],"has":[200],"advantages":[201],"over":[202],"state-of-the-art":[204],"approaches.":[205]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":2},{"year":2022,"cited_by_count":2},{"year":2021,"cited_by_count":3},{"year":2020,"cited_by_count":1},{"year":2019,"cited_by_count":5},{"year":2018,"cited_by_count":6},{"year":2017,"cited_by_count":8},{"year":2016,"cited_by_count":4}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
