{"id":"https://openalex.org/W2028790949","doi":"https://doi.org/10.1109/igarss.2012.6351027","title":"Automated grain sizing using mark-based watershed algorithm","display_name":"Automated grain sizing using mark-based watershed algorithm","publication_year":2012,"publication_date":"2012-07-01","ids":{"openalex":"https://openalex.org/W2028790949","doi":"https://doi.org/10.1109/igarss.2012.6351027","mag":"2028790949"},"language":"en","primary_location":{"id":"doi:10.1109/igarss.2012.6351027","is_oa":false,"landing_page_url":"https://doi.org/10.1109/igarss.2012.6351027","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2012 IEEE International Geoscience and Remote Sensing Symposium","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/A5112485573","display_name":"Han-Sheng Chuang","orcid":null},"institutions":[{"id":"https://openalex.org/I91807558","display_name":"National Cheng Kung University","ror":"https://ror.org/01b8kcc49","country_code":"TW","type":"education","lineage":["https://openalex.org/I91807558"]}],"countries":["TW"],"is_corresponding":false,"raw_author_name":"Han-Sheng Chuang","raw_affiliation_strings":["Department of Geomatics, National Cheng Kung University, Tainan, Taiwan","Dept. of Geomatics, Nat. Cheng Kung Univ., Tainan, Taiwan"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Geomatics, National Cheng Kung University, Tainan, Taiwan","institution_ids":["https://openalex.org/I91807558"]},{"raw_affiliation_string":"Dept. of Geomatics, Nat. Cheng Kung Univ., Tainan, Taiwan","institution_ids":["https://openalex.org/I91807558"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5056190602","display_name":"Chao\u2010Hung Lin","orcid":"https://orcid.org/0000-0001-8126-8794"},"institutions":[{"id":"https://openalex.org/I91807558","display_name":"National Cheng Kung University","ror":"https://ror.org/01b8kcc49","country_code":"TW","type":"education","lineage":["https://openalex.org/I91807558"]}],"countries":["TW"],"is_corresponding":false,"raw_author_name":"Chao-Hung Lin","raw_affiliation_strings":["Department of Geomatics, National Cheng Kung University, Tainan, Taiwan","Dept. of Geomatics, Nat. Cheng Kung Univ., Tainan, Taiwan"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Geomatics, National Cheng Kung University, Tainan, Taiwan","institution_ids":["https://openalex.org/I91807558"]},{"raw_affiliation_string":"Dept. of Geomatics, Nat. Cheng Kung Univ., Tainan, Taiwan","institution_ids":["https://openalex.org/I91807558"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":3,"citation_normalized_percentile":{"value":0.10395509,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":95},"biblio":{"volume":null,"issue":null,"first_page":"2332","last_page":"2335"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12549","display_name":"Image and Object Detection Techniques","score":0.9986000061035156,"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":0.9986000061035156,"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/T14339","display_name":"Image Processing and 3D Reconstruction","score":0.9975000023841858,"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":0.9843000173568726,"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/watershed","display_name":"Watershed","score":0.7860164642333984},{"id":"https://openalex.org/keywords/maxima-and-minima","display_name":"Maxima and minima","score":0.7132379412651062},{"id":"https://openalex.org/keywords/sizing","display_name":"Sizing","score":0.677135705947876},{"id":"https://openalex.org/keywords/ellipse","display_name":"Ellipse","score":0.6609808802604675},{"id":"https://openalex.org/keywords/a-priori-and-a-posteriori","display_name":"A priori and a posteriori","score":0.6105266809463501},{"id":"https://openalex.org/keywords/pixel","display_name":"Pixel","score":0.6005363464355469},{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.5851011276245117},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5822771787643433},{"id":"https://openalex.org/keywords/image-segmentation","display_name":"Image segmentation","score":0.5522465705871582},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.49756887555122375},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.47320932149887085},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.3993915617465973},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.3402918577194214},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.25172728300094604},{"id":"https://openalex.org/keywords/geometry","display_name":"Geometry","score":0.1295543909072876}],"concepts":[{"id":"https://openalex.org/C150547873","wikidata":"https://www.wikidata.org/wiki/Q947851","display_name":"Watershed","level":2,"score":0.7860164642333984},{"id":"https://openalex.org/C186633575","wikidata":"https://www.wikidata.org/wiki/Q845060","display_name":"Maxima and minima","level":2,"score":0.7132379412651062},{"id":"https://openalex.org/C2777767291","wikidata":"https://www.wikidata.org/wiki/Q1080291","display_name":"Sizing","level":2,"score":0.677135705947876},{"id":"https://openalex.org/C74261601","wikidata":"https://www.wikidata.org/wiki/Q40112","display_name":"Ellipse","level":2,"score":0.6609808802604675},{"id":"https://openalex.org/C75553542","wikidata":"https://www.wikidata.org/wiki/Q178161","display_name":"A priori and a posteriori","level":2,"score":0.6105266809463501},{"id":"https://openalex.org/C160633673","wikidata":"https://www.wikidata.org/wiki/Q355198","display_name":"Pixel","level":2,"score":0.6005363464355469},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.5851011276245117},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5822771787643433},{"id":"https://openalex.org/C124504099","wikidata":"https://www.wikidata.org/wiki/Q56933","display_name":"Image segmentation","level":3,"score":0.5522465705871582},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.49756887555122375},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.47320932149887085},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3993915617465973},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.3402918577194214},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.25172728300094604},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.1295543909072876},{"id":"https://openalex.org/C111472728","wikidata":"https://www.wikidata.org/wiki/Q9471","display_name":"Epistemology","level":1,"score":0.0},{"id":"https://openalex.org/C142362112","wikidata":"https://www.wikidata.org/wiki/Q735","display_name":"Art","level":0,"score":0.0},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C153349607","wikidata":"https://www.wikidata.org/wiki/Q36649","display_name":"Visual arts","level":1,"score":0.0},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/igarss.2012.6351027","is_oa":false,"landing_page_url":"https://doi.org/10.1109/igarss.2012.6351027","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2012 IEEE International Geoscience and Remote Sensing Symposium","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Life in Land","score":0.7200000286102295,"id":"https://metadata.un.org/sdg/15"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":8,"referenced_works":["https://openalex.org/W1585431621","https://openalex.org/W1694567288","https://openalex.org/W2061585120","https://openalex.org/W2099356348","https://openalex.org/W2111116530","https://openalex.org/W2124260943","https://openalex.org/W2145023731","https://openalex.org/W6634966438"],"related_works":["https://openalex.org/W2371136327","https://openalex.org/W4293234107","https://openalex.org/W2375684291","https://openalex.org/W2370549269","https://openalex.org/W2386824811","https://openalex.org/W2375311683","https://openalex.org/W2354618530","https://openalex.org/W2081226903","https://openalex.org/W2363452175","https://openalex.org/W2366062860"],"abstract_inverted_index":{"This":[0],"paper":[1],"presents":[2],"a":[3,46],"method":[4],"based":[5],"on":[6],"mark-based":[7],"watershed":[8,61],"algorithm":[9],"to":[10,52],"automatically":[11],"extract":[12],"grains":[13,30,64],"and":[14,31,79],"determine":[15],"grain":[16,86],"sizes":[17],"from":[18],"images.":[19],"Markers":[20],"generated":[21],"by":[22,90],"the":[23,55,71,77,83],"proposed":[24],"approaches":[25],"represent":[26],"rough":[27],"locations":[28],"of":[29,34,57,85],"aperture.":[32],"Instead":[33],"selecting":[35],"pixels":[36],"with":[37,45],"local":[38],"minima":[39],"as":[40],"marks,":[41],"we":[42],"select":[43],"markers":[44],"priori":[47],"knowledge,":[48],"enabling":[49],"our":[50],"approach":[51],"efficiently":[53],"ease":[54],"problem":[56],"over-segmentation":[58],"in":[59],"traditional":[60],"algorithm.":[62],"The":[63],"patches":[65,74],"are":[66],"extracted":[67],"correctly":[68],"after":[69],"merging":[70],"other":[72],"fragmental":[73],"using":[75],"both":[76],"color":[78],"shape":[80],"properties.":[81],"Finally,":[82],"distribution":[84],"size":[87],"is":[88],"calculated":[89],"fitting":[91],"an":[92],"ellipse":[93],"for":[94],"each":[95],"detected":[96],"grain.":[97]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2023,"cited_by_count":1},{"year":2021,"cited_by_count":1}],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}