{"id":"https://openalex.org/W1881816393","doi":"https://doi.org/10.1109/icassp.1987.1169555","title":"Image coding based on segmentation using region growing","display_name":"Image coding based on segmentation using region growing","publication_year":2005,"publication_date":"2005-03-24","ids":{"openalex":"https://openalex.org/W1881816393","doi":"https://doi.org/10.1109/icassp.1987.1169555","mag":"1881816393"},"language":"en","primary_location":{"id":"doi:10.1109/icassp.1987.1169555","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icassp.1987.1169555","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ICASSP '87. 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/A5036139688","display_name":"K. S. Thyagarajan","orcid":null},"institutions":[{"id":"https://openalex.org/I26538001","display_name":"San Diego State University","ror":"https://ror.org/0264fdx42","country_code":"US","type":"education","lineage":["https://openalex.org/I26538001"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"K. Thyagarajan","raw_affiliation_strings":["ECE Department, SDSU, San Diego, CA, USA"],"affiliations":[{"raw_affiliation_string":"ECE Department, SDSU, San Diego, CA, USA","institution_ids":["https://openalex.org/I26538001"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5006043370","display_name":"H. Bohlmann","orcid":null},"institutions":[{"id":"https://openalex.org/I26538001","display_name":"San Diego State University","ror":"https://ror.org/0264fdx42","country_code":"US","type":"education","lineage":["https://openalex.org/I26538001"]},{"id":"https://openalex.org/I114112103","display_name":"Leibniz University Hannover","ror":"https://ror.org/0304hq317","country_code":"DE","type":"education","lineage":["https://openalex.org/I114112103"]}],"countries":["DE","US"],"is_corresponding":false,"raw_author_name":"H. Bohlmann","raw_affiliation_strings":["ECE Department, SDSU, San Diego, USA","Institut fur Allgemeine Nachrichtentechnik, Universitat Hannover, Germany"],"affiliations":[{"raw_affiliation_string":"ECE Department, SDSU, San Diego, USA","institution_ids":["https://openalex.org/I26538001"]},{"raw_affiliation_string":"Institut fur Allgemeine Nachrichtentechnik, Universitat Hannover, Germany","institution_ids":["https://openalex.org/I114112103"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5111882131","display_name":"H. Abut","orcid":null},"institutions":[{"id":"https://openalex.org/I26538001","display_name":"San Diego State University","ror":"https://ror.org/0264fdx42","country_code":"US","type":"education","lineage":["https://openalex.org/I26538001"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"H. Abut","raw_affiliation_strings":["ECE Department, SDSU, San Diego, CA, USA"],"affiliations":[{"raw_affiliation_string":"ECE Department, SDSU, San Diego, CA, USA","institution_ids":["https://openalex.org/I26538001"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5036139688"],"corresponding_institution_ids":["https://openalex.org/I26538001"],"apc_list":null,"apc_paid":null,"fwci":0.2937,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":{"value":0.57441888,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":94},"biblio":{"volume":"12","issue":null,"first_page":"752","last_page":"755"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10901","display_name":"Advanced Data Compression Techniques","score":0.9998000264167786,"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/T10901","display_name":"Advanced Data Compression Techniques","score":0.9998000264167786,"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/T10824","display_name":"Image Retrieval and Classification Techniques","score":0.998199999332428,"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/T10688","display_name":"Image and Signal Denoising Methods","score":0.9977999925613403,"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/codebook","display_name":"Codebook","score":0.787786602973938},{"id":"https://openalex.org/keywords/centroid","display_name":"Centroid","score":0.7535197734832764},{"id":"https://openalex.org/keywords/image-segmentation","display_name":"Image segmentation","score":0.6938285827636719},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6828028559684753},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5917423367500305},{"id":"https://openalex.org/keywords/pixel","display_name":"Pixel","score":0.591325044631958},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.5733028650283813},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5625724792480469},{"id":"https://openalex.org/keywords/coding","display_name":"Coding (social sciences)","score":0.548004150390625},{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.5310293436050415},{"id":"https://openalex.org/keywords/homogeneous","display_name":"Homogeneous","score":0.5135119557380676},{"id":"https://openalex.org/keywords/range-segmentation","display_name":"Range segmentation","score":0.4926057457923889},{"id":"https://openalex.org/keywords/region-growing","display_name":"Region growing","score":0.474802166223526},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.4741106629371643},{"id":"https://openalex.org/keywords/class","display_name":"Class (philosophy)","score":0.4183810353279114},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.32095640897750854},{"id":"https://openalex.org/keywords/image-texture","display_name":"Image texture","score":0.3145689368247986},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.11874726414680481},{"id":"https://openalex.org/keywords/combinatorics","display_name":"Combinatorics","score":0.07173234224319458}],"concepts":[{"id":"https://openalex.org/C127759330","wikidata":"https://www.wikidata.org/wiki/Q637416","display_name":"Codebook","level":2,"score":0.787786602973938},{"id":"https://openalex.org/C146599234","wikidata":"https://www.wikidata.org/wiki/Q511093","display_name":"Centroid","level":2,"score":0.7535197734832764},{"id":"https://openalex.org/C124504099","wikidata":"https://www.wikidata.org/wiki/Q56933","display_name":"Image segmentation","level":3,"score":0.6938285827636719},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6828028559684753},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5917423367500305},{"id":"https://openalex.org/C160633673","wikidata":"https://www.wikidata.org/wiki/Q355198","display_name":"Pixel","level":2,"score":0.591325044631958},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.5733028650283813},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5625724792480469},{"id":"https://openalex.org/C179518139","wikidata":"https://www.wikidata.org/wiki/Q5140297","display_name":"Coding (social sciences)","level":2,"score":0.548004150390625},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.5310293436050415},{"id":"https://openalex.org/C66882249","wikidata":"https://www.wikidata.org/wiki/Q169336","display_name":"Homogeneous","level":2,"score":0.5135119557380676},{"id":"https://openalex.org/C67561299","wikidata":"https://www.wikidata.org/wiki/Q7292710","display_name":"Range segmentation","level":5,"score":0.4926057457923889},{"id":"https://openalex.org/C206824153","wikidata":"https://www.wikidata.org/wiki/Q1169834","display_name":"Region growing","level":5,"score":0.474802166223526},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.4741106629371643},{"id":"https://openalex.org/C2777212361","wikidata":"https://www.wikidata.org/wiki/Q5127848","display_name":"Class (philosophy)","level":2,"score":0.4183810353279114},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.32095640897750854},{"id":"https://openalex.org/C63099799","wikidata":"https://www.wikidata.org/wiki/Q17147001","display_name":"Image texture","level":4,"score":0.3145689368247986},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.11874726414680481},{"id":"https://openalex.org/C114614502","wikidata":"https://www.wikidata.org/wiki/Q76592","display_name":"Combinatorics","level":1,"score":0.07173234224319458}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icassp.1987.1169555","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icassp.1987.1169555","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ICASSP '87. IEEE International Conference on Acoustics, Speech, and Signal Processing","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":4,"referenced_works":["https://openalex.org/W1776627580","https://openalex.org/W2054804336","https://openalex.org/W3100816363","https://openalex.org/W4244017338"],"related_works":["https://openalex.org/W2204605857","https://openalex.org/W2162746041","https://openalex.org/W2360759360","https://openalex.org/W2992675616","https://openalex.org/W3196005494","https://openalex.org/W2799704911","https://openalex.org/W2181571961","https://openalex.org/W4206358120","https://openalex.org/W2188292956","https://openalex.org/W2115198604"],"abstract_inverted_index":{"This":[0],"paper":[1,69],"describes":[2],"a":[3],"composite":[4,94],"source":[5,95],"model":[6],"for":[7,107],"images.":[8],"An":[9],"image":[10,49,63,98],"is":[11,27,50,99],"segmented":[12,48],"into":[13,53],"uniform":[14],"and":[15,81],"homogeneous":[16],"regions":[17,34],"using":[18,101],"centroid":[19],"linkage":[20],"region":[21,25,37,43],"growing":[22,38],"algorithms.":[23],"The":[24,46,62,78],"homogenity":[26],"determined":[28],"by":[29],"the":[30,56,59,75,82,111],"Student":[31],"T-statistics.":[32],"Excessive":[33],"resulting":[35],"from":[36],"are":[39,65,86],"merged":[40],"according":[41],"to":[42],"merging":[44],"rules.":[45],"initially":[47],"then":[51],"clustered":[52],"classes":[54,64],"with":[55,104],"help":[57],"of":[58,93,110],"K-means":[60],"algorithm.":[61],"shown":[66],"in":[67,73],"this":[68],"as":[70,90],"visual":[71],"aids":[72],"judging":[74],"classification":[76],"procedure.":[77],"class":[79,109],"numbers":[80],"corresponding":[83],"pixel":[84],"counts":[85],"also":[87],"included.":[88],"Finally,":[89],"an":[91,97],"application":[92],"models,":[96],"encoded":[100],"matrix":[102],"quantizers":[103],"separate":[105],"codebook":[106],"each":[108],"image.":[112]},"counts_by_year":[{"year":2016,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}