{"id":"https://openalex.org/W2171499486","doi":"https://doi.org/10.1117/1.3429721","title":"Algorithm to measure automatically the ductile/brittle fracture of Charpy test specimens","display_name":"Algorithm to measure automatically the ductile/brittle fracture of Charpy test specimens","publication_year":2010,"publication_date":"2010-04-01","ids":{"openalex":"https://openalex.org/W2171499486","doi":"https://doi.org/10.1117/1.3429721","mag":"2171499486"},"language":"en","primary_location":{"id":"doi:10.1117/1.3429721","is_oa":false,"landing_page_url":"https://doi.org/10.1117/1.3429721","pdf_url":null,"source":{"id":"https://openalex.org/S158511090","display_name":"Journal of Electronic Imaging","issn_l":"1017-9909","issn":["1017-9909","1560-229X"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310315543","host_organization_name":"SPIE","host_organization_lineage":["https://openalex.org/P4310315543"],"host_organization_lineage_names":["SPIE"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Journal of Electronic Imaging","raw_type":"journal-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/A5080619706","display_name":"Andrew J. Tickle","orcid":null},"institutions":[{"id":"https://openalex.org/I146655781","display_name":"University of Liverpool","ror":"https://ror.org/04xs57h96","country_code":"GB","type":"education","lineage":["https://openalex.org/I146655781"]}],"countries":["GB"],"is_corresponding":true,"raw_author_name":"Andrew J. Tickle","raw_affiliation_strings":["Univ. of Liverpool (United Kingdom)"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Univ. of Liverpool (United Kingdom)","institution_ids":["https://openalex.org/I146655781"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":["https://openalex.org/A5080619706"],"corresponding_institution_ids":["https://openalex.org/I146655781"],"apc_list":null,"apc_paid":null,"fwci":0.5094,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":{"value":0.73727866,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":94},"biblio":{"volume":"19","issue":"2","first_page":"023013","last_page":"023013"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12169","display_name":"Non-Destructive Testing Techniques","score":0.9980999827384949,"subfield":{"id":"https://openalex.org/subfields/2210","display_name":"Mechanical Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T12169","display_name":"Non-Destructive Testing Techniques","score":0.9980999827384949,"subfield":{"id":"https://openalex.org/subfields/2210","display_name":"Mechanical 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/T10161","display_name":"Rock Mechanics and Modeling","score":0.9944000244140625,"subfield":{"id":"https://openalex.org/subfields/2211","display_name":"Mechanics of Materials"},"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/T10662","display_name":"Ultrasonics and Acoustic Wave Propagation","score":0.9923999905586243,"subfield":{"id":"https://openalex.org/subfields/2211","display_name":"Mechanics of Materials"},"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/charpy-impact-test","display_name":"Charpy impact test","score":0.8234730362892151},{"id":"https://openalex.org/keywords/brittleness","display_name":"Brittleness","score":0.6166418790817261},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5977016687393188},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5380541682243347},{"id":"https://openalex.org/keywords/preprocessor","display_name":"Preprocessor","score":0.4933301508426666},{"id":"https://openalex.org/keywords/pixel","display_name":"Pixel","score":0.47291550040245056},{"id":"https://openalex.org/keywords/measure","display_name":"Measure (data warehouse)","score":0.4171847701072693},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4052995443344116},{"id":"https://openalex.org/keywords/toughness","display_name":"Toughness","score":0.40050914883613586},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.34014052152633667},{"id":"https://openalex.org/keywords/materials-science","display_name":"Materials science","score":0.2722436785697937},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.13872110843658447},{"id":"https://openalex.org/keywords/composite-material","display_name":"Composite material","score":0.11240282654762268}],"concepts":[{"id":"https://openalex.org/C127205250","wikidata":"https://www.wikidata.org/wiki/Q653604","display_name":"Charpy impact test","level":3,"score":0.8234730362892151},{"id":"https://openalex.org/C136478896","wikidata":"https://www.wikidata.org/wiki/Q898288","display_name":"Brittleness","level":2,"score":0.6166418790817261},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5977016687393188},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5380541682243347},{"id":"https://openalex.org/C34736171","wikidata":"https://www.wikidata.org/wiki/Q918333","display_name":"Preprocessor","level":2,"score":0.4933301508426666},{"id":"https://openalex.org/C160633673","wikidata":"https://www.wikidata.org/wiki/Q355198","display_name":"Pixel","level":2,"score":0.47291550040245056},{"id":"https://openalex.org/C2780009758","wikidata":"https://www.wikidata.org/wiki/Q6804172","display_name":"Measure (data warehouse)","level":2,"score":0.4171847701072693},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4052995443344116},{"id":"https://openalex.org/C99595764","wikidata":"https://www.wikidata.org/wiki/Q486802","display_name":"Toughness","level":2,"score":0.40050914883613586},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.34014052152633667},{"id":"https://openalex.org/C192562407","wikidata":"https://www.wikidata.org/wiki/Q228736","display_name":"Materials science","level":0,"score":0.2722436785697937},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.13872110843658447},{"id":"https://openalex.org/C159985019","wikidata":"https://www.wikidata.org/wiki/Q181790","display_name":"Composite material","level":1,"score":0.11240282654762268}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1117/1.3429721","is_oa":false,"landing_page_url":"https://doi.org/10.1117/1.3429721","pdf_url":null,"source":{"id":"https://openalex.org/S158511090","display_name":"Journal of Electronic Imaging","issn_l":"1017-9909","issn":["1017-9909","1560-229X"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310315543","host_organization_name":"SPIE","host_organization_lineage":["https://openalex.org/P4310315543"],"host_organization_lineage_names":["SPIE"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Journal of Electronic Imaging","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/7","display_name":"Affordable and clean energy","score":0.5799999833106995}],"awards":[],"funders":[{"id":"https://openalex.org/F4320320323","display_name":"University of Liverpool","ror":"https://ror.org/04xs57h96"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":9,"referenced_works":["https://openalex.org/W45589453","https://openalex.org/W1509002716","https://openalex.org/W1994009299","https://openalex.org/W2002478524","https://openalex.org/W2009386811","https://openalex.org/W2034422404","https://openalex.org/W2044465660","https://openalex.org/W2045111985","https://openalex.org/W3120421331"],"related_works":["https://openalex.org/W2359645431","https://openalex.org/W2007615609","https://openalex.org/W842819645","https://openalex.org/W2087916637","https://openalex.org/W2742484459","https://openalex.org/W4226081150","https://openalex.org/W805644668","https://openalex.org/W2969281338","https://openalex.org/W2055083920","https://openalex.org/W2350364579"],"abstract_inverted_index":{"The":[0,12,81],"Charpy":[1],"impact":[2,29],"test":[3,13],"technique":[4],"assesses":[5],"the":[6,15,28,47,54,68,90,134,149,152,157,160,172,191],"toughness":[7,36],"of":[8,17,30,35,49,84,89,151,159,190],"an":[9],"engineering":[10],"material.":[11],"measures":[14],"amount":[16],"energy":[18],"a":[19,31,42,73,86,117,141],"specimen":[20],"can":[21],"resist":[22],"before":[23],"it":[24,98],"is":[25,37,60,64,121,145],"broken":[26],"by":[27,41],"heavy":[32],"pendulum.":[33],"Estimation":[34],"carried":[38],"out":[39],"manually":[40,164,192],"skilled":[43],"operator;":[44],"they":[45],"assess":[46,156],"percentage":[48,150],"light-reflective":[50],"brittle":[51,125,153,180],"regions":[52,183],"on":[53],"fracture":[55,91],"area.":[56],"Because":[57],"this":[58,78],"assessment":[59],"performed":[61,193],"manually,":[62],"there":[63],"some":[65],"subjectivity":[66],"in":[67],"results.":[69],"This":[70],"study":[71],"proposes":[72],"machine-based-learning":[74],"algorithm":[75,173],"to":[76,122,139,147,177],"estimate":[77,132],"measure":[79],"automatically.":[80],"method":[82],"consists":[83],"capturing":[85],"digital":[87],"image":[88],"surface":[92],"after":[93],"impact,":[94],"preprocessing":[95],"it,":[96],"dividing":[97],"up":[99],"into":[100],"10\u00d710":[101],"pixel":[102],"segments,":[103],"and":[104,126,163,181,185],"extracting":[105],"from":[106],"each":[107],"segment":[108],"features":[109],"associated":[110],"with":[111],"its":[112],"texture.":[113],"Feature":[114],"vectors":[115],"feed":[116],"classifier":[118],"whose":[119],"purpose":[120],"distinguish":[123,178],"between":[124,179],"ductile":[127,182],"images":[128,166],"(binary":[129],"output).":[130],"To":[131,155],"toughness,":[133],"classifier's":[135],"outputs":[136],"are":[137,167],"used":[138,188],"construct":[140],"binary":[142],"image,":[143],"which":[144],"postprocessed":[146],"determine":[148],"region.":[154],"accuracy":[158],"algorithm,":[161],"automatically":[162],"classified":[165],"compared.":[168],"Results":[169],"show":[170],"that":[171],"proposed":[174],"was":[175],"able":[176],"successfully":[184],"could":[186],"be":[187],"instead":[189],"technique.":[194]},"counts_by_year":[{"year":2019,"cited_by_count":1},{"year":2012,"cited_by_count":1}],"updated_date":"2026-07-31T08:31:51.225901","created_date":"2025-10-10T00:00:00"}
