{"id":"https://openalex.org/W1671701588","doi":"https://doi.org/10.1109/inista.2015.7276728","title":"Weighted principal component analysis based edge linking","display_name":"Weighted principal component analysis based edge linking","publication_year":2015,"publication_date":"2015-09-01","ids":{"openalex":"https://openalex.org/W1671701588","doi":"https://doi.org/10.1109/inista.2015.7276728","mag":"1671701588"},"language":"en","primary_location":{"id":"doi:10.1109/inista.2015.7276728","is_oa":false,"landing_page_url":"https://doi.org/10.1109/inista.2015.7276728","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2015 International Symposium on Innovations in Intelligent SysTems and Applications (INISTA)","raw_type":"proceedings-article"},"type":"conference-paper","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/A5022999248","display_name":"Kemal \u00d6zkan","orcid":"https://orcid.org/0000-0003-2252-2128"},"institutions":[{"id":"https://openalex.org/I51209816","display_name":"Eski\u015fehir Osmangazi University","ror":"https://ror.org/01dzjez04","country_code":"TR","type":"education","lineage":["https://openalex.org/I51209816"]}],"countries":["TR"],"is_corresponding":false,"raw_author_name":"Kemal Ozkan","raw_affiliation_strings":["Department of Computer Engineering, Eskisehir Osmangazi University, Eskisehir, Turkey"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Computer Engineering, Eskisehir Osmangazi University, Eskisehir, Turkey","institution_ids":["https://openalex.org/I51209816"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5046578097","display_name":"\u015eahin I\u015f\u0131k","orcid":"https://orcid.org/0000-0003-1768-7104"},"institutions":[{"id":"https://openalex.org/I51209816","display_name":"Eski\u015fehir Osmangazi University","ror":"https://ror.org/01dzjez04","country_code":"TR","type":"education","lineage":["https://openalex.org/I51209816"]}],"countries":["TR"],"is_corresponding":false,"raw_author_name":"Sahin Isik","raw_affiliation_strings":["Department of Computer Engineering, Eskisehir Osmangazi University, Eskisehir, Turkey"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Computer Engineering, Eskisehir Osmangazi University, Eskisehir, Turkey","institution_ids":["https://openalex.org/I51209816"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I51209816"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.05634956,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"3","issue":null,"first_page":"1","last_page":"7"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10052","display_name":"Medical Image Segmentation Techniques","score":0.9993000030517578,"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/T10052","display_name":"Medical Image Segmentation Techniques","score":0.9993000030517578,"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/T12549","display_name":"Image and Object Detection 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/T12111","display_name":"Industrial Vision Systems and Defect Detection","score":0.9954000115394592,"subfield":{"id":"https://openalex.org/subfields/2209","display_name":"Industrial and Manufacturing Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/principal-component-analysis","display_name":"Principal component analysis","score":0.7233527898788452},{"id":"https://openalex.org/keywords/enhanced-data-rates-for-gsm-evolution","display_name":"Enhanced Data Rates for GSM Evolution","score":0.6434870362281799},{"id":"https://openalex.org/keywords/noise","display_name":"Noise (video)","score":0.6422609090805054},{"id":"https://openalex.org/keywords/eigenvalues-and-eigenvectors","display_name":"Eigenvalues and eigenvectors","score":0.6271259784698486},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.608753502368927},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5631996393203735},{"id":"https://openalex.org/keywords/edge-detection","display_name":"Edge detection","score":0.5392040610313416},{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.5217536091804504},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.5203761458396912},{"id":"https://openalex.org/keywords/point","display_name":"Point (geometry)","score":0.5084854364395142},{"id":"https://openalex.org/keywords/block","display_name":"Block (permutation group theory)","score":0.4990200996398926},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.49481457471847534},{"id":"https://openalex.org/keywords/robust-principal-component-analysis","display_name":"Robust principal component analysis","score":0.46834060549736023},{"id":"https://openalex.org/keywords/image-segmentation","display_name":"Image segmentation","score":0.4558010399341583},{"id":"https://openalex.org/keywords/connected-component","display_name":"Connected component","score":0.4529517889022827},{"id":"https://openalex.org/keywords/image-processing","display_name":"Image processing","score":0.42794692516326904},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.37936604022979736},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.3705750107765198},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.3446032404899597},{"id":"https://openalex.org/keywords/geometry","display_name":"Geometry","score":0.18395453691482544},{"id":"https://openalex.org/keywords/physics","display_name":"Physics","score":0.06565079092979431}],"concepts":[{"id":"https://openalex.org/C27438332","wikidata":"https://www.wikidata.org/wiki/Q2873","display_name":"Principal component analysis","level":2,"score":0.7233527898788452},{"id":"https://openalex.org/C162307627","wikidata":"https://www.wikidata.org/wiki/Q204833","display_name":"Enhanced Data Rates for GSM Evolution","level":2,"score":0.6434870362281799},{"id":"https://openalex.org/C99498987","wikidata":"https://www.wikidata.org/wiki/Q2210247","display_name":"Noise (video)","level":3,"score":0.6422609090805054},{"id":"https://openalex.org/C158693339","wikidata":"https://www.wikidata.org/wiki/Q190524","display_name":"Eigenvalues and eigenvectors","level":2,"score":0.6271259784698486},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.608753502368927},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5631996393203735},{"id":"https://openalex.org/C193536780","wikidata":"https://www.wikidata.org/wiki/Q1513153","display_name":"Edge detection","level":4,"score":0.5392040610313416},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.5217536091804504},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.5203761458396912},{"id":"https://openalex.org/C28719098","wikidata":"https://www.wikidata.org/wiki/Q44946","display_name":"Point (geometry)","level":2,"score":0.5084854364395142},{"id":"https://openalex.org/C2777210771","wikidata":"https://www.wikidata.org/wiki/Q4927124","display_name":"Block (permutation group theory)","level":2,"score":0.4990200996398926},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.49481457471847534},{"id":"https://openalex.org/C2777749129","wikidata":"https://www.wikidata.org/wiki/Q17148469","display_name":"Robust principal component analysis","level":3,"score":0.46834060549736023},{"id":"https://openalex.org/C124504099","wikidata":"https://www.wikidata.org/wiki/Q56933","display_name":"Image segmentation","level":3,"score":0.4558010399341583},{"id":"https://openalex.org/C193435613","wikidata":"https://www.wikidata.org/wiki/Q2997928","display_name":"Connected component","level":2,"score":0.4529517889022827},{"id":"https://openalex.org/C9417928","wikidata":"https://www.wikidata.org/wiki/Q1070689","display_name":"Image processing","level":3,"score":0.42794692516326904},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.37936604022979736},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.3705750107765198},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.3446032404899597},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.18395453691482544},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.06565079092979431},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/inista.2015.7276728","is_oa":false,"landing_page_url":"https://doi.org/10.1109/inista.2015.7276728","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2015 International Symposium on Innovations in Intelligent SysTems and Applications (INISTA)","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":21,"referenced_works":["https://openalex.org/W1990773344","https://openalex.org/W2000789130","https://openalex.org/W2000889983","https://openalex.org/W2003370853","https://openalex.org/W2010353754","https://openalex.org/W2024032168","https://openalex.org/W2061585120","https://openalex.org/W2098434088","https://openalex.org/W2103938522","https://openalex.org/W2106234561","https://openalex.org/W2116216752","https://openalex.org/W2121927366","https://openalex.org/W2133059825","https://openalex.org/W2145023731","https://openalex.org/W2164323537","https://openalex.org/W2166249153","https://openalex.org/W2341642790","https://openalex.org/W2547114149","https://openalex.org/W2902600303","https://openalex.org/W4285719527","https://openalex.org/W6680096826"],"related_works":["https://openalex.org/W4283792950","https://openalex.org/W2549425886","https://openalex.org/W2124460284","https://openalex.org/W2563483704","https://openalex.org/W3124370832","https://openalex.org/W3003801099","https://openalex.org/W2003667605","https://openalex.org/W62130100","https://openalex.org/W1980960407","https://openalex.org/W2976999964"],"abstract_inverted_index":{"As":[0],"a":[1,11,31],"complicated":[2],"and":[3,24,80,98,107,127,130],"troublesome":[4],"research":[5],"area,":[6],"the":[7,39,42,51,57,61,64,71,74,78,89,92,96,115,123],"edge":[8,35,53],"detection":[9],"is":[10,67,118],"fundamental":[12],"step":[13],"in":[14],"terms":[15],"of":[16,41,47,125],"some":[17,103],"image":[18,126],"processing":[19],"tasks":[20],"including":[21],"segmentation,":[22],"compression":[23],"registration.":[25],"In":[26],"this":[27],"study,":[28],"we":[29,111],"present":[30],"new":[32],"approach":[33],"for":[34],"linking":[36],"by":[37,59,87],"applying":[38],"concept":[40],"PCA":[43,65],"on":[44,70,105],"different":[45],"types":[46],"images":[48],"to":[49,95,120],"determine":[50,56],"attractive":[52],"segments.":[54],"To":[55],"direction":[58],"using":[60],"angle":[62,90],"information,":[63],"decomposition":[66],"carried":[68],"out":[69],"block":[72],"around":[73],"processed":[75],"point.":[76],"Specifically,":[77],"horizontal":[79],"vertical":[81],"directions":[82],"are":[83],"taken":[84],"into":[85],"account":[86],"considering":[88],"between":[91],"eigenvectors":[93],"corresponding":[94],"largest":[97],"smallest":[99],"eigenvalues.":[100],"After":[101],"making":[102],"experiments":[104],"noisy":[106],"noise":[108],"free":[109],"images,":[110],"have":[112],"observed":[113],"that":[114],"proposed":[116],"method":[117],"robust":[119],"noise,":[121],"preserves":[122],"structure":[124],"extracts":[128],"well-localized":[129],"straight":[131],"lines.":[132]},"counts_by_year":[],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2025-10-10T00:00:00"}