{"id":"https://openalex.org/W1572149217","doi":"https://doi.org/10.1109/icassp.1985.1168294","title":"Fast object segmentation in textured backgrouds","display_name":"Fast object segmentation in textured backgrouds","publication_year":2005,"publication_date":"2005-03-23","ids":{"openalex":"https://openalex.org/W1572149217","doi":"https://doi.org/10.1109/icassp.1985.1168294","mag":"1572149217"},"language":"en","primary_location":{"id":"doi:10.1109/icassp.1985.1168294","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icassp.1985.1168294","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ICASSP '85. IEEE International Conference on Acoustics, Speech, and Signal Processing","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/A5086246477","display_name":"Jorge L. C. Sanz","orcid":null},"institutions":[{"id":"https://openalex.org/I1341412227","display_name":"IBM (United States)","ror":"https://ror.org/05hh8d621","country_code":"US","type":"company","lineage":["https://openalex.org/I1341412227"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"J. Sanz","raw_affiliation_strings":["Computer Science Department, IBM Research Laboratory, San Jose, CA, USA","IBM Research laboratory, San Jose, California"],"affiliations":[{"raw_affiliation_string":"Computer Science Department, IBM Research Laboratory, San Jose, CA, USA","institution_ids":["https://openalex.org/I1341412227"]},{"raw_affiliation_string":"IBM Research laboratory, San Jose, California","institution_ids":["https://openalex.org/I1341412227"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":["https://openalex.org/A5086246477"],"corresponding_institution_ids":["https://openalex.org/I1341412227"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.06582068,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"10","issue":null,"first_page":"905","last_page":"908"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12549","display_name":"Image and Object Detection Techniques","score":1.0,"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/T12549","display_name":"Image and Object Detection Techniques","score":1.0,"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":0.9987999796867371,"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"}},{"id":"https://openalex.org/T13114","display_name":"Image Processing Techniques and Applications","score":0.9976000189781189,"subfield":{"id":"https://openalex.org/subfields/2214","display_name":"Media Technology"},"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/computer-science","display_name":"Computer science","score":0.815645694732666},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.7326551675796509},{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.712764322757721},{"id":"https://openalex.org/keywords/thresholding","display_name":"Thresholding","score":0.699571967124939},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.6862300038337708},{"id":"https://openalex.org/keywords/pipeline","display_name":"Pipeline (software)","score":0.6569830775260925},{"id":"https://openalex.org/keywords/image-segmentation","display_name":"Image segmentation","score":0.6352418661117554},{"id":"https://openalex.org/keywords/cluster-analysis","display_name":"Cluster analysis","score":0.5844749808311462},{"id":"https://openalex.org/keywords/object-detection","display_name":"Object detection","score":0.5751345753669739},{"id":"https://openalex.org/keywords/object","display_name":"Object (grammar)","score":0.5231465101242065},{"id":"https://openalex.org/keywords/segmentation-based-object-categorization","display_name":"Segmentation-based object categorization","score":0.5226849317550659},{"id":"https://openalex.org/keywords/scale-space-segmentation","display_name":"Scale-space segmentation","score":0.5121626853942871},{"id":"https://openalex.org/keywords/market-segmentation","display_name":"Market segmentation","score":0.47995904088020325},{"id":"https://openalex.org/keywords/implementation","display_name":"Implementation","score":0.4460059404373169},{"id":"https://openalex.org/keywords/image-processing","display_name":"Image processing","score":0.4224367141723633},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.2772497534751892}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.815645694732666},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7326551675796509},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.712764322757721},{"id":"https://openalex.org/C191178318","wikidata":"https://www.wikidata.org/wiki/Q2256906","display_name":"Thresholding","level":3,"score":0.699571967124939},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.6862300038337708},{"id":"https://openalex.org/C43521106","wikidata":"https://www.wikidata.org/wiki/Q2165493","display_name":"Pipeline (software)","level":2,"score":0.6569830775260925},{"id":"https://openalex.org/C124504099","wikidata":"https://www.wikidata.org/wiki/Q56933","display_name":"Image segmentation","level":3,"score":0.6352418661117554},{"id":"https://openalex.org/C73555534","wikidata":"https://www.wikidata.org/wiki/Q622825","display_name":"Cluster analysis","level":2,"score":0.5844749808311462},{"id":"https://openalex.org/C2776151529","wikidata":"https://www.wikidata.org/wiki/Q3045304","display_name":"Object detection","level":3,"score":0.5751345753669739},{"id":"https://openalex.org/C2781238097","wikidata":"https://www.wikidata.org/wiki/Q175026","display_name":"Object (grammar)","level":2,"score":0.5231465101242065},{"id":"https://openalex.org/C25694479","wikidata":"https://www.wikidata.org/wiki/Q7446278","display_name":"Segmentation-based object categorization","level":5,"score":0.5226849317550659},{"id":"https://openalex.org/C65885262","wikidata":"https://www.wikidata.org/wiki/Q7429708","display_name":"Scale-space segmentation","level":4,"score":0.5121626853942871},{"id":"https://openalex.org/C125308379","wikidata":"https://www.wikidata.org/wiki/Q363057","display_name":"Market segmentation","level":2,"score":0.47995904088020325},{"id":"https://openalex.org/C26713055","wikidata":"https://www.wikidata.org/wiki/Q245962","display_name":"Implementation","level":2,"score":0.4460059404373169},{"id":"https://openalex.org/C9417928","wikidata":"https://www.wikidata.org/wiki/Q1070689","display_name":"Image processing","level":3,"score":0.4224367141723633},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.2772497534751892},{"id":"https://openalex.org/C144133560","wikidata":"https://www.wikidata.org/wiki/Q4830453","display_name":"Business","level":0,"score":0.0},{"id":"https://openalex.org/C162853370","wikidata":"https://www.wikidata.org/wiki/Q39809","display_name":"Marketing","level":1,"score":0.0},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icassp.1985.1168294","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icassp.1985.1168294","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ICASSP '85. IEEE International Conference on Acoustics, Speech, and Signal Processing","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Industry, innovation and infrastructure","score":0.41999998688697815,"id":"https://metadata.un.org/sdg/9"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":12,"referenced_works":["https://openalex.org/W1974748191","https://openalex.org/W1986266833","https://openalex.org/W2002811962","https://openalex.org/W2025573053","https://openalex.org/W2028973780","https://openalex.org/W2033849769","https://openalex.org/W2041276914","https://openalex.org/W2069610368","https://openalex.org/W2095175361","https://openalex.org/W2144215166","https://openalex.org/W2169349346","https://openalex.org/W4321072212"],"related_works":["https://openalex.org/W3144569342","https://openalex.org/W2185902295","https://openalex.org/W2945274617","https://openalex.org/W2372421320","https://openalex.org/W2057775483","https://openalex.org/W2041871225","https://openalex.org/W2386644571","https://openalex.org/W2387793296","https://openalex.org/W1558398159","https://openalex.org/W2371519352"],"abstract_inverted_index":{"In":[0],"this":[1],"paper,":[2],"we":[3,25],"deal":[4],"with":[5],"the":[6,39,43,46,87,90],"problem":[7],"of":[8,34,41,58,89],"detecting":[9],"and":[10,45,74],"segmenting":[11],"objects":[12],"in":[13,67],"textured":[14],"darkfield":[15],"digital":[16],"imagery":[17],"for":[18],"automated":[19],"visual":[20],"inspection":[21],"applications.":[22,83],"The":[23],"technique":[24,92],"will":[26,93],"follow":[27],"is":[28,77],"based":[29],"on":[30],"a":[31],"sequential":[32],"application":[33],"local":[35],"operators":[36],"which":[37],"serves":[38],"purpose":[40,69],"clustering":[42],"object":[44],"background":[47],"gray":[48],"levels.":[49],"This":[50,62],"procedure":[51],"can":[52],"be":[53,94],"considered":[54],"as":[55],"an":[56],"extension":[57],"average-thresholding":[59],"type":[60],"techniques.":[61],"algorithm":[63],"has":[64],"fast":[65],"implementations":[66],"general":[68],"image":[70],"processing":[71],"pipeline":[72],"architectures":[73],"therefore,":[75],"it":[76],"appealing":[78],"to":[79],"real-time":[80],"computer":[81],"vision":[82],"Computational":[84],"examples":[85],"showing":[86],"effectiveness":[88],"segmentation":[91],"discussed.":[95]},"counts_by_year":[],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
