{"id":"https://openalex.org/W2511023051","doi":"https://doi.org/10.1109/icip.2016.7533021","title":"Structure tensor Log-Euclidean statistical models for texture analysis","display_name":"Structure tensor Log-Euclidean statistical models for texture analysis","publication_year":2016,"publication_date":"2016-08-17","ids":{"openalex":"https://openalex.org/W2511023051","doi":"https://doi.org/10.1109/icip.2016.7533021","mag":"2511023051"},"language":"en","primary_location":{"id":"doi:10.1109/icip.2016.7533021","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icip.2016.7533021","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2016 IEEE International Conference on Image Processing (ICIP)","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/A5078940725","display_name":"Roxana-Gabriela Rosu","orcid":null},"institutions":[{"id":"https://openalex.org/I4210157089","display_name":"Laboratoire de l'Int\u00e9gration du Mat\u00e9riau au Syst\u00e8me","ror":"https://ror.org/04nabhy78","country_code":"FR","type":"facility","lineage":["https://openalex.org/I1294671590","https://openalex.org/I1294671590","https://openalex.org/I15057530","https://openalex.org/I4210091158","https://openalex.org/I4210095849","https://openalex.org/I4210157089","https://openalex.org/I4210160189"]},{"id":"https://openalex.org/I4210160189","display_name":"Institut Polytechnique de Bordeaux","ror":"https://ror.org/054qv7y42","country_code":"FR","type":"education","lineage":["https://openalex.org/I4210160189"]}],"countries":["FR"],"is_corresponding":false,"raw_author_name":"Roxana-Gabriela Rosu","raw_affiliation_strings":["UMR 5218, IMS, Talence, France"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"UMR 5218, IMS, Talence, France","institution_ids":["https://openalex.org/I4210157089","https://openalex.org/I4210160189"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5073184327","display_name":"Jean\u2010Pierre da Costa","orcid":"https://orcid.org/0000-0003-2390-0047"},"institutions":[{"id":"https://openalex.org/I1294671590","display_name":"Centre National de la Recherche Scientifique","ror":"https://ror.org/02feahw73","country_code":"FR","type":"government","lineage":["https://openalex.org/I1294671590"]},{"id":"https://openalex.org/I4210157089","display_name":"Laboratoire de l'Int\u00e9gration du Mat\u00e9riau au Syst\u00e8me","ror":"https://ror.org/04nabhy78","country_code":"FR","type":"facility","lineage":["https://openalex.org/I1294671590","https://openalex.org/I1294671590","https://openalex.org/I15057530","https://openalex.org/I4210091158","https://openalex.org/I4210095849","https://openalex.org/I4210157089","https://openalex.org/I4210160189"]},{"id":"https://openalex.org/I4210160189","display_name":"Institut Polytechnique de Bordeaux","ror":"https://ror.org/054qv7y42","country_code":"FR","type":"education","lineage":["https://openalex.org/I4210160189"]}],"countries":["FR"],"is_corresponding":false,"raw_author_name":"Jean-Pierre Da Costa","raw_affiliation_strings":["CNRS, UMR 5218, Talence, France"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"CNRS, UMR 5218, Talence, France","institution_ids":["https://openalex.org/I4210157089","https://openalex.org/I4210160189","https://openalex.org/I1294671590"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5074358807","display_name":"Marc Donias","orcid":null},"institutions":[{"id":"https://openalex.org/I4210160189","display_name":"Institut Polytechnique de Bordeaux","ror":"https://ror.org/054qv7y42","country_code":"FR","type":"education","lineage":["https://openalex.org/I4210160189"]}],"countries":["FR"],"is_corresponding":false,"raw_author_name":"Marc Donias","raw_affiliation_strings":["Bordeaux INP, IMS, Talence, France"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Bordeaux INP, IMS, Talence, France","institution_ids":["https://openalex.org/I4210160189"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.3315,"has_fulltext":false,"cited_by_count":3,"citation_normalized_percentile":{"value":0.65726475,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":94},"biblio":{"volume":"35","issue":null,"first_page":"3553","last_page":"3557"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10824","display_name":"Image Retrieval and Classification Techniques","score":0.9994999766349792,"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":0.9994999766349792,"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":0.9944999814033508,"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/T10627","display_name":"Advanced Image and Video Retrieval Techniques","score":0.9901000261306763,"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/euclidean-geometry","display_name":"Euclidean geometry","score":0.5666642785072327},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.553429365158081},{"id":"https://openalex.org/keywords/tensor","display_name":"Tensor (intrinsic definition)","score":0.5516975522041321},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5353928208351135},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.512643039226532},{"id":"https://openalex.org/keywords/structure-tensor","display_name":"Structure tensor","score":0.49096038937568665},{"id":"https://openalex.org/keywords/image-texture","display_name":"Image texture","score":0.48381370306015015},{"id":"https://openalex.org/keywords/context","display_name":"Context (archaeology)","score":0.477979838848114},{"id":"https://openalex.org/keywords/anisotropy","display_name":"Anisotropy","score":0.46281540393829346},{"id":"https://openalex.org/keywords/texture","display_name":"Texture (cosmology)","score":0.4592364728450775},{"id":"https://openalex.org/keywords/gaussian","display_name":"Gaussian","score":0.44213706254959106},{"id":"https://openalex.org/keywords/invariant","display_name":"Invariant (physics)","score":0.43846091628074646},{"id":"https://openalex.org/keywords/euclidean-distance","display_name":"Euclidean distance","score":0.41077566146850586},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.3994094133377075},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.32940375804901123},{"id":"https://openalex.org/keywords/image-processing","display_name":"Image processing","score":0.296109139919281},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.23714745044708252},{"id":"https://openalex.org/keywords/geology","display_name":"Geology","score":0.13384094834327698},{"id":"https://openalex.org/keywords/physics","display_name":"Physics","score":0.1159687340259552},{"id":"https://openalex.org/keywords/geometry","display_name":"Geometry","score":0.11002963781356812},{"id":"https://openalex.org/keywords/optics","display_name":"Optics","score":0.09292465448379517}],"concepts":[{"id":"https://openalex.org/C129782007","wikidata":"https://www.wikidata.org/wiki/Q162886","display_name":"Euclidean geometry","level":2,"score":0.5666642785072327},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.553429365158081},{"id":"https://openalex.org/C155281189","wikidata":"https://www.wikidata.org/wiki/Q3518150","display_name":"Tensor (intrinsic definition)","level":2,"score":0.5516975522041321},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5353928208351135},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.512643039226532},{"id":"https://openalex.org/C113315163","wikidata":"https://www.wikidata.org/wiki/Q7625159","display_name":"Structure tensor","level":3,"score":0.49096038937568665},{"id":"https://openalex.org/C63099799","wikidata":"https://www.wikidata.org/wiki/Q17147001","display_name":"Image texture","level":4,"score":0.48381370306015015},{"id":"https://openalex.org/C2779343474","wikidata":"https://www.wikidata.org/wiki/Q3109175","display_name":"Context (archaeology)","level":2,"score":0.477979838848114},{"id":"https://openalex.org/C85725439","wikidata":"https://www.wikidata.org/wiki/Q466686","display_name":"Anisotropy","level":2,"score":0.46281540393829346},{"id":"https://openalex.org/C2781195486","wikidata":"https://www.wikidata.org/wiki/Q289436","display_name":"Texture (cosmology)","level":3,"score":0.4592364728450775},{"id":"https://openalex.org/C163716315","wikidata":"https://www.wikidata.org/wiki/Q901177","display_name":"Gaussian","level":2,"score":0.44213706254959106},{"id":"https://openalex.org/C190470478","wikidata":"https://www.wikidata.org/wiki/Q2370229","display_name":"Invariant (physics)","level":2,"score":0.43846091628074646},{"id":"https://openalex.org/C120174047","wikidata":"https://www.wikidata.org/wiki/Q847073","display_name":"Euclidean distance","level":2,"score":0.41077566146850586},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.3994094133377075},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.32940375804901123},{"id":"https://openalex.org/C9417928","wikidata":"https://www.wikidata.org/wiki/Q1070689","display_name":"Image processing","level":3,"score":0.296109139919281},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.23714745044708252},{"id":"https://openalex.org/C127313418","wikidata":"https://www.wikidata.org/wiki/Q1069","display_name":"Geology","level":0,"score":0.13384094834327698},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.1159687340259552},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.11002963781356812},{"id":"https://openalex.org/C120665830","wikidata":"https://www.wikidata.org/wiki/Q14620","display_name":"Optics","level":1,"score":0.09292465448379517},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0},{"id":"https://openalex.org/C151730666","wikidata":"https://www.wikidata.org/wiki/Q7205","display_name":"Paleontology","level":1,"score":0.0},{"id":"https://openalex.org/C37914503","wikidata":"https://www.wikidata.org/wiki/Q156495","display_name":"Mathematical physics","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/icip.2016.7533021","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icip.2016.7533021","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2016 IEEE International Conference on Image Processing (ICIP)","raw_type":"proceedings-article"},{"id":"pmh:oai:HAL:hal-01471648v1","is_oa":false,"landing_page_url":"https://hal.science/hal-01471648","pdf_url":null,"source":{"id":"https://openalex.org/S4306402512","display_name":"HAL (Le Centre pour la Communication Scientifique Directe)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1294671590","host_organization_name":"Centre National de la Recherche Scientifique","host_organization_lineage":["https://openalex.org/I1294671590"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"23th IEEE International Conference on Image Processing (ICIP 2016), Sep 2016, Phoenix, United States. pp.3553-3557, ⟨10.1109/ICIP.2016.7533021⟩","raw_type":"info:eu-repo/semantics/conferenceObject"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/14","score":0.8799999952316284,"display_name":"Life below water"}],"awards":[],"funders":[{"id":"https://openalex.org/F4320321519","display_name":"Centre National d\u2019Etudes Spatiales","ror":"https://ror.org/04h1h0y33"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":23,"referenced_works":["https://openalex.org/W1542873368","https://openalex.org/W1545934923","https://openalex.org/W1577152977","https://openalex.org/W1601669748","https://openalex.org/W1738112110","https://openalex.org/W1978563338","https://openalex.org/W1981560592","https://openalex.org/W2006825873","https://openalex.org/W2020459435","https://openalex.org/W2044465660","https://openalex.org/W2044981864","https://openalex.org/W2048192550","https://openalex.org/W2090334843","https://openalex.org/W2112759033","https://openalex.org/W2122673410","https://openalex.org/W2125148312","https://openalex.org/W2163534628","https://openalex.org/W2180940127","https://openalex.org/W2900649085","https://openalex.org/W2963167705","https://openalex.org/W3021628422","https://openalex.org/W6637754412","https://openalex.org/W6996289242"],"related_works":["https://openalex.org/W89301254","https://openalex.org/W2623954137","https://openalex.org/W2090152127","https://openalex.org/W1965169884","https://openalex.org/W3125580510","https://openalex.org/W2008939113","https://openalex.org/W2015754241","https://openalex.org/W14679004","https://openalex.org/W1566651525","https://openalex.org/W2977652649"],"abstract_inverted_index":{"This":[0],"paper":[1],"presents":[2],"local":[3],"structure":[4],"tensor":[5],"(LST)":[6],"based":[7,65],"methods":[8],"for":[9,29,48],"extracting":[10],"the":[11,31,35],"anisotropy":[12],"and":[13,89],"orientation":[14],"information":[15],"characterizing":[16],"a":[17,39,61],"textured":[18],"image":[19,66],"sample.":[20],"A":[21],"Log-Euclidean":[22],"(LE)":[23],"multivariate":[24],"Gaussian":[25],"model":[26,43],"is":[27,44],"proposed":[28],"representing":[30,92],"marginal":[32],"distribution":[33],"of":[34,38,55],"LST":[36],"field":[37],"texture.":[40],"An":[41],"extended":[42],"considered":[45],"as":[46],"well":[47],"describing":[49],"its":[50],"spatial":[51],"dependencies.":[52],"The":[53],"potential":[54],"these":[56],"approaches":[57],"are":[58,71],"tested":[59],"in":[60],"rotation":[62],"invariant":[63],"content":[64],"retrieval":[67],"(CBIR)":[68],"context.":[69],"Experiments":[70],"conducted":[72],"on":[73],"real":[74],"data":[75],"presenting":[76],"anisotropic":[77],"textures:":[78],"very":[79],"high":[80],"resolution":[81],"(VHR)":[82],"remote":[83],"sensing":[84],"maritime":[85],"pine":[86],"forest":[87],"images":[88,91],"material":[90],"dense":[93],"carbons":[94],"at":[95],"nanometric":[96],"scale.":[97]},"counts_by_year":[{"year":2020,"cited_by_count":1},{"year":2019,"cited_by_count":1},{"year":2018,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}