{"id":"https://openalex.org/W4402280566","doi":"https://doi.org/10.3390/s24175762","title":"Target Fitting Method for Spherical Point Clouds Based on Projection Filtering and K-Means Clustered Voxelization","display_name":"Target Fitting Method for Spherical Point Clouds Based on Projection Filtering and K-Means Clustered Voxelization","publication_year":2024,"publication_date":"2024-09-04","ids":{"openalex":"https://openalex.org/W4402280566","doi":"https://doi.org/10.3390/s24175762","pmid":"https://pubmed.ncbi.nlm.nih.gov/39275673"},"language":"en","primary_location":{"id":"doi:10.3390/s24175762","is_oa":true,"landing_page_url":"https://doi.org/10.3390/s24175762","pdf_url":"https://www.mdpi.com/1424-8220/24/17/5762/pdf?version=1725521821","source":{"id":"https://openalex.org/S101949793","display_name":"Sensors","issn_l":"1424-8220","issn":["1424-8220"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Sensors","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj","pubmed"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://www.mdpi.com/1424-8220/24/17/5762/pdf?version=1725521821","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5112177860","display_name":"Zhe Wang","orcid":"https://orcid.org/0009-0005-0633-2238"},"institutions":[{"id":"https://openalex.org/I55538621","display_name":"China Jiliang University","ror":"https://ror.org/05v1y0t93","country_code":"CN","type":"education","lineage":["https://openalex.org/I55538621"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhe Wang","raw_affiliation_strings":["Key Laboratory of In-Situ Metrology, Ministry of Education, China Jiliang University, Hangzhou 310018, China"],"affiliations":[{"raw_affiliation_string":"Key Laboratory of In-Situ Metrology, Ministry of Education, China Jiliang University, Hangzhou 310018, China","institution_ids":["https://openalex.org/I55538621"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5039517432","display_name":"Jiacheng Hu","orcid":null},"institutions":[{"id":"https://openalex.org/I55538621","display_name":"China Jiliang University","ror":"https://ror.org/05v1y0t93","country_code":"CN","type":"education","lineage":["https://openalex.org/I55538621"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Jiacheng Hu","raw_affiliation_strings":["Key Laboratory of In-Situ Metrology, Ministry of Education, China Jiliang University, Hangzhou 310018, China"],"affiliations":[{"raw_affiliation_string":"Key Laboratory of In-Situ Metrology, Ministry of Education, China Jiliang University, Hangzhou 310018, China","institution_ids":["https://openalex.org/I55538621"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101890832","display_name":"Yushu Shi","orcid":"https://orcid.org/0000-0002-7445-9952"},"institutions":[{"id":"https://openalex.org/I4210162136","display_name":"National Institute of Metrology","ror":"https://ror.org/05dw0p167","country_code":"CN","type":"other","lineage":["https://openalex.org/I4210162136"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yushu Shi","raw_affiliation_strings":["National Institute of Metrology, Beijing 102200, China"],"affiliations":[{"raw_affiliation_string":"National Institute of Metrology, Beijing 102200, China","institution_ids":["https://openalex.org/I4210162136"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5102023189","display_name":"Jinhui Cai","orcid":"https://orcid.org/0000-0003-2881-2927"},"institutions":[{"id":"https://openalex.org/I55538621","display_name":"China Jiliang University","ror":"https://ror.org/05v1y0t93","country_code":"CN","type":"education","lineage":["https://openalex.org/I55538621"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jinhui Cai","raw_affiliation_strings":["Key Laboratory of In-Situ Metrology, Ministry of Education, China Jiliang University, Hangzhou 310018, China"],"affiliations":[{"raw_affiliation_string":"Key Laboratory of In-Situ Metrology, Ministry of Education, China Jiliang University, Hangzhou 310018, China","institution_ids":["https://openalex.org/I55538621"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5055218789","display_name":"Lei Pi","orcid":null},"institutions":[{"id":"https://openalex.org/I4210162136","display_name":"National Institute of Metrology","ror":"https://ror.org/05dw0p167","country_code":"CN","type":"other","lineage":["https://openalex.org/I4210162136"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Lei Pi","raw_affiliation_strings":["National Institute of Metrology, Beijing 102200, China"],"affiliations":[{"raw_affiliation_string":"National Institute of Metrology, Beijing 102200, China","institution_ids":["https://openalex.org/I4210162136"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5039517432"],"corresponding_institution_ids":["https://openalex.org/I55538621"],"apc_list":{"value":2400,"currency":"CHF","value_usd":2598},"apc_paid":{"value":2400,"currency":"CHF","value_usd":2598},"fwci":0.5761,"has_fulltext":true,"cited_by_count":3,"citation_normalized_percentile":{"value":0.63624483,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":95,"max":99},"biblio":{"volume":"24","issue":"17","first_page":"5762","last_page":"5762"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12386","display_name":"Advanced X-ray and CT Imaging","score":0.996999979019165,"subfield":{"id":"https://openalex.org/subfields/2204","display_name":"Biomedical Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T12386","display_name":"Advanced X-ray and CT Imaging","score":0.996999979019165,"subfield":{"id":"https://openalex.org/subfields/2204","display_name":"Biomedical 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/T12549","display_name":"Image and Object Detection Techniques","score":0.9939000010490417,"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/T10052","display_name":"Medical Image Segmentation Techniques","score":0.9889000058174133,"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/ransac","display_name":"RANSAC","score":0.9564131498336792},{"id":"https://openalex.org/keywords/robustness","display_name":"Robustness (evolution)","score":0.719964861869812},{"id":"https://openalex.org/keywords/point-cloud","display_name":"Point cloud","score":0.6286436319351196},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.5607356429100037},{"id":"https://openalex.org/keywords/standard-deviation","display_name":"Standard deviation","score":0.544571042060852},{"id":"https://openalex.org/keywords/cluster-analysis","display_name":"Cluster analysis","score":0.5073344111442566},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.48945605754852295},{"id":"https://openalex.org/keywords/projection","display_name":"Projection (relational algebra)","score":0.44595953822135925},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.3885965049266815},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.3775012195110321},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.13522523641586304},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.09446772933006287}],"concepts":[{"id":"https://openalex.org/C114744707","wikidata":"https://www.wikidata.org/wiki/Q218533","display_name":"RANSAC","level":3,"score":0.9564131498336792},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.719964861869812},{"id":"https://openalex.org/C131979681","wikidata":"https://www.wikidata.org/wiki/Q1899648","display_name":"Point cloud","level":2,"score":0.6286436319351196},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.5607356429100037},{"id":"https://openalex.org/C22679943","wikidata":"https://www.wikidata.org/wiki/Q159375","display_name":"Standard deviation","level":2,"score":0.544571042060852},{"id":"https://openalex.org/C73555534","wikidata":"https://www.wikidata.org/wiki/Q622825","display_name":"Cluster analysis","level":2,"score":0.5073344111442566},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.48945605754852295},{"id":"https://openalex.org/C57493831","wikidata":"https://www.wikidata.org/wiki/Q3134666","display_name":"Projection (relational algebra)","level":2,"score":0.44595953822135925},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3885965049266815},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.3775012195110321},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.13522523641586304},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.09446772933006287},{"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/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.0}],"mesh":[],"locations_count":4,"locations":[{"id":"doi:10.3390/s24175762","is_oa":true,"landing_page_url":"https://doi.org/10.3390/s24175762","pdf_url":"https://www.mdpi.com/1424-8220/24/17/5762/pdf?version=1725521821","source":{"id":"https://openalex.org/S101949793","display_name":"Sensors","issn_l":"1424-8220","issn":["1424-8220"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Sensors","raw_type":"journal-article"},{"id":"pmid:39275673","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/39275673","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":"Sensors (Basel, Switzerland)","raw_type":null},{"id":"pmh:oai:pubmedcentral.nih.gov:11398214","is_oa":true,"landing_page_url":"https://www.ncbi.nlm.nih.gov/pmc/articles/11398214","pdf_url":"https://pmc.ncbi.nlm.nih.gov/articles/PMC11398214/pdf/sensors-24-05762.pdf","source":{"id":"https://openalex.org/S2764455111","display_name":"PubMed Central","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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Sensors (Basel)","raw_type":"Text"},{"id":"pmh:oai:doaj.org/article:3100836eefcd43d1a6c8e2efa0d7a51b","is_oa":true,"landing_page_url":"https://doaj.org/article/3100836eefcd43d1a6c8e2efa0d7a51b","pdf_url":null,"source":{"id":"https://openalex.org/S112646816","display_name":"SHILAP Revista de lepidopterolog\u00eda","issn_l":"0300-5267","issn":["0300-5267","2340-4078"],"is_oa":true,"is_in_doaj":true,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Sensors, Vol 24, Iss 17, p 5762 (2024)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.3390/s24175762","is_oa":true,"landing_page_url":"https://doi.org/10.3390/s24175762","pdf_url":"https://www.mdpi.com/1424-8220/24/17/5762/pdf?version=1725521821","source":{"id":"https://openalex.org/S101949793","display_name":"Sensors","issn_l":"1424-8220","issn":["1424-8220"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Sensors","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":true,"grobid_xml":false},"content_urls":{"pdf":"https://content.openalex.org/works/W4402280566.pdf"},"referenced_works_count":37,"referenced_works":["https://openalex.org/W1948600975","https://openalex.org/W2000018820","https://openalex.org/W2017776197","https://openalex.org/W2030579064","https://openalex.org/W2035850930","https://openalex.org/W2072451751","https://openalex.org/W2087448796","https://openalex.org/W2091286770","https://openalex.org/W2490247310","https://openalex.org/W2528677474","https://openalex.org/W2547174479","https://openalex.org/W2776796896","https://openalex.org/W2893269394","https://openalex.org/W2911995813","https://openalex.org/W2972346427","https://openalex.org/W3048729674","https://openalex.org/W3188159124","https://openalex.org/W3212903447","https://openalex.org/W4200542874","https://openalex.org/W4206335957","https://openalex.org/W4281670948","https://openalex.org/W4292451577","https://openalex.org/W4308572394","https://openalex.org/W4313032049","https://openalex.org/W4319988723","https://openalex.org/W4320712954","https://openalex.org/W4321060805","https://openalex.org/W4321252637","https://openalex.org/W4388694405","https://openalex.org/W4391484814","https://openalex.org/W4392455391","https://openalex.org/W4392602126","https://openalex.org/W4394582151","https://openalex.org/W4396680631","https://openalex.org/W4399677186","https://openalex.org/W6848852644","https://openalex.org/W6849701445"],"related_works":["https://openalex.org/W2131378265","https://openalex.org/W2984240274","https://openalex.org/W3107042705","https://openalex.org/W2981196697","https://openalex.org/W3083084699","https://openalex.org/W2115876589","https://openalex.org/W3012182724","https://openalex.org/W1988708904","https://openalex.org/W3171899115","https://openalex.org/W3126266918"],"abstract_inverted_index":{"Industrial":[0],"computed":[1],"tomography":[2],"(CT)":[3],"is":[4,71,187,215],"widely":[5],"used":[6],"in":[7,36,49,59,78],"the":[8,37,50,60,82,88,95,110,160,163,173],"measurement":[9],"field":[10],"owing":[11],"to":[12,44,142,189],"its":[13],"advantages":[14],"such":[15,46],"as":[16,47],"non-contact":[17],"and":[18,91,109,130,137,146,170,180,233],"high":[19],"precision.":[20],"To":[21,114],"obtain":[22,190],"accurate":[23,191],"size":[24],"parameters,":[25],"fitting":[26,103,124,192,207,237],"parameters":[27],"can":[28],"be":[29],"obtained":[30,63],"rapidly":[31],"by":[32,74,178],"processing":[33],"volume":[34],"data":[35],"form":[38],"of":[39,81,84,112,162,209,221],"point":[40,61,122,176],"clouds.":[41],"However,":[42],"due":[43],"factors":[45],"artifacts":[48],"CT":[51],"reconstruction":[52],"process,":[53],"many":[54],"abnormal":[55],"interference":[56],"points":[57],"exist":[58],"clouds":[62],"after":[64],"segmentation.":[65],"The":[66,148,184,204,224],"classic":[67],"least":[68],"squares":[69],"algorithm":[70,125],"easily":[72],"affected":[73],"these":[75,116,139],"points,":[76],"resulting":[77],"significant":[79],"deviation":[80,161,208],"solution":[83],"linear":[85],"equations":[86],"from":[87],"normal":[89],"value":[90,220],"poor":[92],"robustness,":[93],"while":[94],"random":[96],"sample":[97],"consensus":[98],"(RANSAC)":[99],"approach":[100],"has":[101,230],"insufficient":[102],"accuracy":[104,145,232],"within":[105],"a":[106,120,196,200],"limited":[107],"timeframe":[108],"number":[111],"iterations.":[113],"address":[115],"shortcomings,":[117],"we":[118],"propose":[119],"spherical":[121,164,174],"cloud":[123],"based":[126],"on":[127],"projection":[128],"filtering":[129],"K-Means":[131,182],"clustering":[132],"(PK-RANSAC),":[133],"which":[134,214],"strategically":[135],"integrates":[136],"enhances":[138],"two":[140],"methods":[141],"achieve":[143],"excellent":[144],"robustness.":[147],"proposed":[149],"method":[150],"first":[151],"uses":[152],"RANSAC":[153],"for":[154,236],"rough":[155],"parameter":[156],"estimation,":[157],"then":[158],"corrects":[159],"center":[165,175,206],"coordinates":[166],"through":[167],"two-dimensional":[168],"projection,":[169],"finally":[171],"obtains":[172],"set":[177],"sampling":[179],"performing":[181],"clustering.":[183],"largest":[185],"cluster":[186],"weighted":[188],"parameters.":[193,239],"We":[194],"conducted":[195],"comparative":[197],"experiment":[198],"using":[199],"three-dimensional":[201],"ball-plate":[202],"standard.":[203],"sphere":[205],"PK-RANSAC":[210,229],"was":[211],"1.91":[212],"\u03bcm,":[213],"significantly":[216],"better":[217],"than":[218],"RANSAC's":[219],"25.41":[222],"\u03bcm.":[223],"experimental":[225],"results":[226],"demonstrate":[227],"that":[228],"higher":[231],"stronger":[234],"robustness":[235],"geometric":[238]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":2}],"updated_date":"2026-03-11T06:11:40.159057","created_date":"2025-10-10T00:00:00"}
