{"id":"https://openalex.org/W2095804880","doi":"https://doi.org/10.1109/isspa.2005.1581024","title":"Texture classification using gabor energy features and higher order spectral features: a comparative study","display_name":"Texture classification using gabor energy features and higher order spectral features: a comparative study","publication_year":2006,"publication_date":"2006-10-04","ids":{"openalex":"https://openalex.org/W2095804880","doi":"https://doi.org/10.1109/isspa.2005.1581024","mag":"2095804880"},"language":"en","primary_location":{"id":"doi:10.1109/isspa.2005.1581024","is_oa":false,"landing_page_url":"https://doi.org/10.1109/isspa.2005.1581024","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the Eighth International Symposium on Signal Processing and Its Applications, 2005.","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/A5007093329","display_name":"Ronald Tabu Elunai","orcid":null},"institutions":[{"id":"https://openalex.org/I160993911","display_name":"Queensland University of Technology","ror":"https://ror.org/03pnv4752","country_code":"AU","type":"education","lineage":["https://openalex.org/I160993911"]}],"countries":["AU"],"is_corresponding":true,"raw_author_name":"R. Elunai","raw_affiliation_strings":["Speech, Audio, Image and Video Research Laboratory, Queensland University of Technology, Brisbane, Australia"],"affiliations":[{"raw_affiliation_string":"Speech, Audio, Image and Video Research Laboratory, Queensland University of Technology, Brisbane, Australia","institution_ids":["https://openalex.org/I160993911"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5001328179","display_name":"Vinod Chandran","orcid":"https://orcid.org/0000-0003-3185-0852"},"institutions":[{"id":"https://openalex.org/I160993911","display_name":"Queensland University of Technology","ror":"https://ror.org/03pnv4752","country_code":"AU","type":"education","lineage":["https://openalex.org/I160993911"]}],"countries":["AU"],"is_corresponding":false,"raw_author_name":"V. Chandran","raw_affiliation_strings":["Speech, Audio, Image and Video Research Laboratory, Queensland University of Technology, Brisbane, Australia"],"affiliations":[{"raw_affiliation_string":"Speech, Audio, Image and Video Research Laboratory, Queensland University of Technology, Brisbane, Australia","institution_ids":["https://openalex.org/I160993911"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5110003534","display_name":"S. Sridharan","orcid":null},"institutions":[{"id":"https://openalex.org/I160993911","display_name":"Queensland University of Technology","ror":"https://ror.org/03pnv4752","country_code":"AU","type":"education","lineage":["https://openalex.org/I160993911"]}],"countries":["AU"],"is_corresponding":false,"raw_author_name":"S. Sridharan","raw_affiliation_strings":["Speech, Audio, Image and Video Research Laboratory, Queensland University of Technology, Brisbane, Australia"],"affiliations":[{"raw_affiliation_string":"Speech, Audio, Image and Video Research Laboratory, Queensland University of Technology, Brisbane, Australia","institution_ids":["https://openalex.org/I160993911"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5007093329"],"corresponding_institution_ids":["https://openalex.org/I160993911"],"apc_list":null,"apc_paid":null,"fwci":0.3114,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":{"value":0.60300014,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":94},"biblio":{"volume":"2","issue":null,"first_page":"659","last_page":"662"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10824","display_name":"Image Retrieval and Classification Techniques","score":0.9987999796867371,"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/T10824","display_name":"Image Retrieval and Classification Techniques","score":0.9987999796867371,"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/T10640","display_name":"Spectroscopy and Chemometric Analyses","score":0.9901999831199646,"subfield":{"id":"https://openalex.org/subfields/1602","display_name":"Analytical Chemistry"},"field":{"id":"https://openalex.org/fields/16","display_name":"Chemistry"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10057","display_name":"Face and Expression Recognition","score":0.9876000285148621,"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":0.8091795444488525},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.8033760786056519},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.7154849767684937},{"id":"https://openalex.org/keywords/texture","display_name":"Texture (cosmology)","score":0.6535813808441162},{"id":"https://openalex.org/keywords/invariant","display_name":"Invariant (physics)","score":0.6229094862937927},{"id":"https://openalex.org/keywords/gabor-filter","display_name":"Gabor filter","score":0.612959623336792},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5862834453582764},{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.5176694393157959},{"id":"https://openalex.org/keywords/support-vector-machine","display_name":"Support vector machine","score":0.5124655365943909},{"id":"https://openalex.org/keywords/image-texture","display_name":"Image texture","score":0.5106599926948547},{"id":"https://openalex.org/keywords/contrast","display_name":"Contrast (vision)","score":0.4224206507205963},{"id":"https://openalex.org/keywords/gabor-wavelet","display_name":"Gabor wavelet","score":0.41780099272727966},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.41258031129837036},{"id":"https://openalex.org/keywords/energy","display_name":"Energy (signal processing)","score":0.4101608991622925},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.3259495496749878},{"id":"https://openalex.org/keywords/image-segmentation","display_name":"Image segmentation","score":0.3071552515029907},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.1517372727394104},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.07963237166404724},{"id":"https://openalex.org/keywords/wavelet-transform","display_name":"Wavelet transform","score":0.055573105812072754}],"concepts":[{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.8091795444488525},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.8033760786056519},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.7154849767684937},{"id":"https://openalex.org/C2781195486","wikidata":"https://www.wikidata.org/wiki/Q289436","display_name":"Texture (cosmology)","level":3,"score":0.6535813808441162},{"id":"https://openalex.org/C190470478","wikidata":"https://www.wikidata.org/wiki/Q2370229","display_name":"Invariant (physics)","level":2,"score":0.6229094862937927},{"id":"https://openalex.org/C2779883129","wikidata":"https://www.wikidata.org/wiki/Q2447890","display_name":"Gabor filter","level":3,"score":0.612959623336792},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5862834453582764},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.5176694393157959},{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.5124655365943909},{"id":"https://openalex.org/C63099799","wikidata":"https://www.wikidata.org/wiki/Q17147001","display_name":"Image texture","level":4,"score":0.5106599926948547},{"id":"https://openalex.org/C2776502983","wikidata":"https://www.wikidata.org/wiki/Q690182","display_name":"Contrast (vision)","level":2,"score":0.4224206507205963},{"id":"https://openalex.org/C136902061","wikidata":"https://www.wikidata.org/wiki/Q16981559","display_name":"Gabor wavelet","level":5,"score":0.41780099272727966},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.41258031129837036},{"id":"https://openalex.org/C186370098","wikidata":"https://www.wikidata.org/wiki/Q442787","display_name":"Energy (signal processing)","level":2,"score":0.4101608991622925},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.3259495496749878},{"id":"https://openalex.org/C124504099","wikidata":"https://www.wikidata.org/wiki/Q56933","display_name":"Image segmentation","level":3,"score":0.3071552515029907},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.1517372727394104},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.07963237166404724},{"id":"https://openalex.org/C196216189","wikidata":"https://www.wikidata.org/wiki/Q2867","display_name":"Wavelet transform","level":3,"score":0.055573105812072754},{"id":"https://openalex.org/C37914503","wikidata":"https://www.wikidata.org/wiki/Q156495","display_name":"Mathematical physics","level":1,"score":0.0},{"id":"https://openalex.org/C46286280","wikidata":"https://www.wikidata.org/wiki/Q2414958","display_name":"Discrete wavelet transform","level":4,"score":0.0},{"id":"https://openalex.org/C47432892","wikidata":"https://www.wikidata.org/wiki/Q831390","display_name":"Wavelet","level":2,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/isspa.2005.1581024","is_oa":false,"landing_page_url":"https://doi.org/10.1109/isspa.2005.1581024","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the Eighth International Symposium on Signal Processing and Its Applications, 2005.","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/7","display_name":"Affordable and clean energy","score":0.6600000262260437}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":23,"referenced_works":["https://openalex.org/W586876317","https://openalex.org/W623020896","https://openalex.org/W1487718662","https://openalex.org/W1509814203","https://openalex.org/W1563088657","https://openalex.org/W2006500012","https://openalex.org/W2026946351","https://openalex.org/W2031586513","https://openalex.org/W2096127742","https://openalex.org/W2098347925","https://openalex.org/W2106778119","https://openalex.org/W2108995755","https://openalex.org/W2110482401","https://openalex.org/W2114755071","https://openalex.org/W2120846928","https://openalex.org/W2131268110","https://openalex.org/W2139212933","https://openalex.org/W2153366199","https://openalex.org/W2156909104","https://openalex.org/W2163676538","https://openalex.org/W2169369279","https://openalex.org/W4233104424","https://openalex.org/W6630374904"],"related_works":["https://openalex.org/W2070838085","https://openalex.org/W2374740620","https://openalex.org/W2495360253","https://openalex.org/W1811332408","https://openalex.org/W2518455383","https://openalex.org/W2066448268","https://openalex.org/W2559560477","https://openalex.org/W2009069257","https://openalex.org/W2228937159","https://openalex.org/W3016960874"],"abstract_inverted_index":{"Several":[0],"approaches":[1,37],"to":[2,65],"the":[3,51,75,88,98],"classification":[4,24,81],"and":[5,44,60,106],"segmentation":[6],"of":[7,21,50,97],"textural":[8],"content":[9],"in":[10,16,56],"digital":[11],"images":[12],"have":[13],"been":[14],"investigated":[15],"recent":[17],"years.":[18],"The":[19],"extraction":[20,40],"features":[22,67,78],"for":[23,38,83,107],"has":[25],"particularly":[26],"received":[27],"considerable":[28],"attention.":[29],"In":[30],"this":[31],"paper":[32],"we":[33],"contrast":[34],"between":[35],"two":[36,99],"feature":[39,100],"i.e.":[41],"Gabor":[42,89],"filters":[43],"bispectral":[45,76],"invariant":[46,77],"features.":[47],"A":[48],"subset":[49],"Brodatz":[52],"album":[53],"are":[54,63],"used":[55],"a":[57,95],"dichotomy":[58],"experiment":[59],"separate":[61],"SVMs":[62],"trained":[64],"classify":[66],"from":[68],"each":[69],"pair.":[70],"Our":[71],"experiments":[72],"show":[73],"that":[74,94],"produce":[79],"better":[80],"results":[82],"more":[84],"texture":[85,109],"pairs":[86],"than":[87],"filters.":[90],"Results":[91],"also":[92],"indicate":[93],"combination":[96],"sets":[101],"will":[102],"yield":[103],"higher":[104],"accuracy,":[105],"some":[108],"pairs,":[110],"neither":[111],"works":[112],"very":[113],"well.":[114]},"counts_by_year":[{"year":2017,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
