{"id":"https://openalex.org/W4289922182","doi":"https://doi.org/10.1109/access.2022.3196788","title":"Textural Analysis for Medicinal Plants Identification Using Log Gabor Filters","display_name":"Textural Analysis for Medicinal Plants Identification Using Log Gabor Filters","publication_year":2022,"publication_date":"2022-01-01","ids":{"openalex":"https://openalex.org/W4289922182","doi":"https://doi.org/10.1109/access.2022.3196788"},"language":"en","primary_location":{"id":"doi:10.1109/access.2022.3196788","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2022.3196788","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/6514899/09850987.pdf","source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://ieeexplore.ieee.org/ielx7/6287639/6514899/09850987.pdf","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5076345517","display_name":"Frimpong Twum","orcid":"https://orcid.org/0000-0002-1869-7542"},"institutions":[{"id":"https://openalex.org/I28046988","display_name":"Kwame Nkrumah University of Science and Technology","ror":"https://ror.org/00cb23x68","country_code":"GH","type":"education","lineage":["https://openalex.org/I28046988"]}],"countries":["GH"],"is_corresponding":true,"raw_author_name":"Frimpong Twum","raw_affiliation_strings":["Department of Computer Science, Kwame Nkrumah University of Science and Technology, Kumasi, Ghana"],"raw_orcid":"https://orcid.org/0000-0002-1869-7542","affiliations":[{"raw_affiliation_string":"Department of Computer Science, Kwame Nkrumah University of Science and Technology, Kumasi, Ghana","institution_ids":["https://openalex.org/I28046988"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5075557431","display_name":"Yaw Marfo Missah","orcid":"https://orcid.org/0000-0002-2926-681X"},"institutions":[{"id":"https://openalex.org/I28046988","display_name":"Kwame Nkrumah University of Science and Technology","ror":"https://ror.org/00cb23x68","country_code":"GH","type":"education","lineage":["https://openalex.org/I28046988"]}],"countries":["GH"],"is_corresponding":false,"raw_author_name":"Yaw Marfo Missah","raw_affiliation_strings":["Department of Computer Science, Kwame Nkrumah University of Science and Technology, Kumasi, Ghana"],"raw_orcid":"https://orcid.org/0000-0002-2926-681X","affiliations":[{"raw_affiliation_string":"Department of Computer Science, Kwame Nkrumah University of Science and Technology, Kumasi, Ghana","institution_ids":["https://openalex.org/I28046988"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5072359636","display_name":"Stephen Opoku Oppong","orcid":"https://orcid.org/0000-0002-1024-5680"},"institutions":[{"id":"https://openalex.org/I145876445","display_name":"University of Education, Winneba","ror":"https://ror.org/00y1ekh28","country_code":"GH","type":"education","lineage":["https://openalex.org/I145876445"]}],"countries":["GH"],"is_corresponding":false,"raw_author_name":"Stephen Opoku Oppong","raw_affiliation_strings":["Department of ICT Education, University of Education, Winneba, Ghana"],"raw_orcid":"https://orcid.org/0000-0002-1024-5680","affiliations":[{"raw_affiliation_string":"Department of ICT Education, University of Education, Winneba, Ghana","institution_ids":["https://openalex.org/I145876445"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5058559943","display_name":"Ussiph Najim","orcid":null},"institutions":[{"id":"https://openalex.org/I28046988","display_name":"Kwame Nkrumah University of Science and Technology","ror":"https://ror.org/00cb23x68","country_code":"GH","type":"education","lineage":["https://openalex.org/I28046988"]}],"countries":["GH"],"is_corresponding":false,"raw_author_name":"Najim Ussiph","raw_affiliation_strings":["Department of Computer Science, Kwame Nkrumah University of Science and Technology, Kumasi, Ghana"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Computer Science, Kwame Nkrumah University of Science and Technology, Kumasi, Ghana","institution_ids":["https://openalex.org/I28046988"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5076345517"],"corresponding_institution_ids":["https://openalex.org/I28046988"],"apc_list":{"value":1850,"currency":"USD","value_usd":1850},"apc_paid":{"value":1850,"currency":"USD","value_usd":1850},"fwci":4.6211,"has_fulltext":true,"cited_by_count":26,"citation_normalized_percentile":{"value":0.9421126,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":94,"max":100},"biblio":{"volume":"10","issue":null,"first_page":"83204","last_page":"83220"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10616","display_name":"Smart Agriculture and AI","score":0.9990000128746033,"subfield":{"id":"https://openalex.org/subfields/1110","display_name":"Plant Science"},"field":{"id":"https://openalex.org/fields/11","display_name":"Agricultural and Biological Sciences"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}},"topics":[{"id":"https://openalex.org/T10616","display_name":"Smart Agriculture and AI","score":0.9990000128746033,"subfield":{"id":"https://openalex.org/subfields/1110","display_name":"Plant Science"},"field":{"id":"https://openalex.org/fields/11","display_name":"Agricultural and Biological Sciences"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}},{"id":"https://openalex.org/T10640","display_name":"Spectroscopy and Chemometric Analyses","score":0.9850999712944031,"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/T14365","display_name":"Leaf Properties and Growth Measurement","score":0.9384999871253967,"subfield":{"id":"https://openalex.org/subfields/1110","display_name":"Plant Science"},"field":{"id":"https://openalex.org/fields/11","display_name":"Agricultural and Biological Sciences"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/gabor-filter","display_name":"Gabor filter","score":0.7848793268203735},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.7111371159553528},{"id":"https://openalex.org/keywords/naive-bayes-classifier","display_name":"Naive Bayes classifier","score":0.6970596313476562},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.695393979549408},{"id":"https://openalex.org/keywords/support-vector-machine","display_name":"Support vector machine","score":0.5945762991905212},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5477936267852783},{"id":"https://openalex.org/keywords/multilayer-perceptron","display_name":"Multilayer perceptron","score":0.5307398438453674},{"id":"https://openalex.org/keywords/random-forest","display_name":"Random forest","score":0.5140991806983948},{"id":"https://openalex.org/keywords/perceptron","display_name":"Perceptron","score":0.46273717284202576},{"id":"https://openalex.org/keywords/histogram","display_name":"Histogram","score":0.44762465357780457},{"id":"https://openalex.org/keywords/filter","display_name":"Filter (signal processing)","score":0.4423925280570984},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.42994821071624756},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.2997998297214508},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.2710617184638977},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.20388314127922058},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.15323275327682495}],"concepts":[{"id":"https://openalex.org/C2779883129","wikidata":"https://www.wikidata.org/wiki/Q2447890","display_name":"Gabor filter","level":3,"score":0.7848793268203735},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7111371159553528},{"id":"https://openalex.org/C52001869","wikidata":"https://www.wikidata.org/wiki/Q812530","display_name":"Naive Bayes classifier","level":3,"score":0.6970596313476562},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.695393979549408},{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.5945762991905212},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5477936267852783},{"id":"https://openalex.org/C179717631","wikidata":"https://www.wikidata.org/wiki/Q2991667","display_name":"Multilayer perceptron","level":3,"score":0.5307398438453674},{"id":"https://openalex.org/C169258074","wikidata":"https://www.wikidata.org/wiki/Q245748","display_name":"Random forest","level":2,"score":0.5140991806983948},{"id":"https://openalex.org/C60908668","wikidata":"https://www.wikidata.org/wiki/Q690207","display_name":"Perceptron","level":3,"score":0.46273717284202576},{"id":"https://openalex.org/C53533937","wikidata":"https://www.wikidata.org/wiki/Q185020","display_name":"Histogram","level":3,"score":0.44762465357780457},{"id":"https://openalex.org/C106131492","wikidata":"https://www.wikidata.org/wiki/Q3072260","display_name":"Filter (signal processing)","level":2,"score":0.4423925280570984},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.42994821071624756},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.2997998297214508},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.2710617184638977},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.20388314127922058},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.15323275327682495}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/access.2022.3196788","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2022.3196788","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/6514899/09850987.pdf","source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},{"id":"pmh:oai:doaj.org/article:5b5fc0203e9e4620ac2b56f033f1faad","is_oa":true,"landing_page_url":"https://doaj.org/article/5b5fc0203e9e4620ac2b56f033f1faad","pdf_url":null,"source":{"id":"https://openalex.org/S4306401280","display_name":"DOAJ (DOAJ: Directory of Open Access Journals)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by-sa","license_id":"https://openalex.org/licenses/cc-by-sa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"IEEE Access, Vol 10, Pp 83204-83220 (2022)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.1109/access.2022.3196788","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2022.3196788","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/6514899/09850987.pdf","source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},"sustainable_development_goals":[{"score":0.7400000095367432,"display_name":"Life in Land","id":"https://metadata.un.org/sdg/15"}],"awards":[],"funders":[],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4289922182.pdf","grobid_xml":"https://content.openalex.org/works/W4289922182.grobid-xml"},"referenced_works_count":76,"referenced_works":["https://openalex.org/W3822628","https://openalex.org/W645748567","https://openalex.org/W1508585575","https://openalex.org/W1521726165","https://openalex.org/W1560071024","https://openalex.org/W1615787874","https://openalex.org/W1852849178","https://openalex.org/W1962010357","https://openalex.org/W1968896562","https://openalex.org/W1970366469","https://openalex.org/W2003400461","https://openalex.org/W2012093028","https://openalex.org/W2050480977","https://openalex.org/W2098532194","https://openalex.org/W2102372511","https://openalex.org/W2114351767","https://openalex.org/W2134672310","https://openalex.org/W2139107690","https://openalex.org/W2169856283","https://openalex.org/W2230508580","https://openalex.org/W2395952108","https://openalex.org/W2406709078","https://openalex.org/W2466367677","https://openalex.org/W2520893792","https://openalex.org/W2531191966","https://openalex.org/W2555330755","https://openalex.org/W2568155635","https://openalex.org/W2581582247","https://openalex.org/W2606543828","https://openalex.org/W2620180909","https://openalex.org/W2621789928","https://openalex.org/W2787219651","https://openalex.org/W2888728157","https://openalex.org/W2895238724","https://openalex.org/W2902013328","https://openalex.org/W2903220284","https://openalex.org/W2907648650","https://openalex.org/W2913054853","https://openalex.org/W2939569677","https://openalex.org/W2954936648","https://openalex.org/W2955016451","https://openalex.org/W2982211640","https://openalex.org/W2988779004","https://openalex.org/W2990346675","https://openalex.org/W2994159190","https://openalex.org/W2995098893","https://openalex.org/W3007004976","https://openalex.org/W3013330736","https://openalex.org/W3013840624","https://openalex.org/W3017314941","https://openalex.org/W3024738743","https://openalex.org/W3025975432","https://openalex.org/W3031656342","https://openalex.org/W3045756608","https://openalex.org/W3049178586","https://openalex.org/W3090710404","https://openalex.org/W3100777112","https://openalex.org/W3109126425","https://openalex.org/W3138539755","https://openalex.org/W3141203463","https://openalex.org/W3175468393","https://openalex.org/W3182554863","https://openalex.org/W3186021667","https://openalex.org/W3201779028","https://openalex.org/W3216366741","https://openalex.org/W4206632396","https://openalex.org/W4211070329","https://openalex.org/W4240740821","https://openalex.org/W4242045199","https://openalex.org/W4248277245","https://openalex.org/W4251672969","https://openalex.org/W4252190344","https://openalex.org/W4252467760","https://openalex.org/W6640974819","https://openalex.org/W6682527921","https://openalex.org/W6731924980"],"related_works":["https://openalex.org/W2076543106","https://openalex.org/W2523437662","https://openalex.org/W89844371","https://openalex.org/W2019891950","https://openalex.org/W2085842814","https://openalex.org/W4286643620","https://openalex.org/W4387048144","https://openalex.org/W2492135063","https://openalex.org/W2362514456","https://openalex.org/W2136232598"],"abstract_inverted_index":{"Texture":[0],"plays":[1],"a":[2,44],"crucial":[3],"role":[4],"in":[5,87,140],"computer":[6],"vision,":[7],"providing":[8],"valuable":[9],"information":[10],"about":[11],"image":[12],"regions.":[13],"Log":[14,75,134,155],"Gabor":[15,76,80,135,138,156,176],"filters":[16],"that":[17],"mimic":[18],"the":[19,35,48,64,79,128,170,175,190],"human":[20],"eye&#x2019;s":[21],"visual":[22],"cortex":[23],"are":[24,71],"used":[25,86],"as":[26,61,63],"feature":[27],"extractors":[28],"to":[29],"identify":[30],"medicinal":[31],"plants":[32],"based":[33],"on":[34,43,92],"leaf":[36],"textural":[37],"features.":[38],"This":[39],"method":[40],"was":[41,160,180],"tested":[42,91],"dataset":[45,173],"developed":[46],"from":[47],"Centre":[49],"of":[50,56,142],"Plant":[51],"Medicine":[52],"Research,":[53],"Ghana,":[54],"consisting":[55],"forty-nine":[57],"(49)":[58],"plant":[59],"species":[60],"well":[62],"Flavia":[65,186],"and":[66,113,124,137,150,167,187],"Swedish":[67,171,191],"Leaf":[68,172,192],"datasets,":[69],"which":[70,82],"benchmark":[72],"datasets.":[73],"The":[74,120,154],"filter":[77,136,139],"outperformed":[78],"filters,":[81],"have":[83],"been":[84],"extensively":[85],"this":[88],"area":[89],"when":[90],"nine":[93],"supervised":[94],"classifiers":[95,131],"(K-Nearest":[96],"Neighbour,":[97],"Support":[98,121],"Vector":[99,122],"Machine,":[100],"Na&#x00EF;ve":[101],"Bayes,":[102],"Logistic":[103],"Regression,":[104],"Decision":[105],"tree,":[106],"Random":[107],"Forest,":[108],"Multilayer":[109,125],"Perceptron,":[110],"Gradient":[111,115],"Boosting":[112],"Stochastic":[114],"Descent)":[116],"with":[117],"10-fold":[118],"cross-validation.":[119],"Machine":[123],"Perceptron":[126],"were":[127],"best":[129],"performing":[130],"for":[132,162,165,169,182,185,189],"both":[133],"terms":[141],"accuracy,":[143],"precision,":[144],"true":[145],"positive":[146,152],"rate,":[147],"F1":[148],"score":[149],"false":[151],"rate.":[153],"filter&#x2019;s":[157,177],"highest":[158,178],"accuracy":[159,179],"79%":[161],"Mydatastet,":[163,183],"97%":[164],"Flavia,":[166],"98%":[168],"whiles":[174],"66%":[181],"92%":[184],"96%":[188],"dataset.":[193]},"counts_by_year":[{"year":2026,"cited_by_count":4},{"year":2025,"cited_by_count":12},{"year":2024,"cited_by_count":3},{"year":2023,"cited_by_count":5},{"year":2022,"cited_by_count":2}],"updated_date":"2026-05-06T08:25:59.206177","created_date":"2025-10-10T00:00:00"}
