{"id":"https://openalex.org/W2561618159","doi":"https://doi.org/10.1109/btas.2016.7791195","title":"PRNU-based image alignment for defective pixel detection","display_name":"PRNU-based image alignment for defective pixel detection","publication_year":2016,"publication_date":"2016-09-01","ids":{"openalex":"https://openalex.org/W2561618159","doi":"https://doi.org/10.1109/btas.2016.7791195","mag":"2561618159"},"language":"en","primary_location":{"id":"doi:10.1109/btas.2016.7791195","is_oa":false,"landing_page_url":"https://doi.org/10.1109/btas.2016.7791195","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2016 IEEE 8th International Conference on Biometrics Theory, Applications and Systems (BTAS)","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/A5037016808","display_name":"Christof Kauba","orcid":"https://orcid.org/0000-0002-2716-1360"},"institutions":[{"id":"https://openalex.org/I182212641","display_name":"University of Salzburg","ror":"https://ror.org/05gs8cd61","country_code":"AT","type":"education","lineage":["https://openalex.org/I182212641"]}],"countries":["AT"],"is_corresponding":false,"raw_author_name":"Christof Kauba","raw_affiliation_strings":["Department of Computer Sciences, University of Salzburg, AUSTRIA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Computer Sciences, University of Salzburg, AUSTRIA","institution_ids":["https://openalex.org/I182212641"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5062946437","display_name":"Andreas Uhl","orcid":"https://orcid.org/0000-0002-5921-8755"},"institutions":[{"id":"https://openalex.org/I182212641","display_name":"University of Salzburg","ror":"https://ror.org/05gs8cd61","country_code":"AT","type":"education","lineage":["https://openalex.org/I182212641"]}],"countries":["AT"],"is_corresponding":false,"raw_author_name":"Andreas Uhl","raw_affiliation_strings":["Department of Computer Sciences, University of Salzburg, AUSTRIA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Computer Sciences, University of Salzburg, AUSTRIA","institution_ids":["https://openalex.org/I182212641"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.338,"has_fulltext":false,"cited_by_count":5,"citation_normalized_percentile":{"value":0.68366575,"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":"1","last_page":"7"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12357","display_name":"Digital Media Forensic Detection","score":0.9998999834060669,"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/T12357","display_name":"Digital Media Forensic Detection","score":0.9998999834060669,"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":0.9975000023841858,"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/T12549","display_name":"Image and Object Detection Techniques","score":0.994700014591217,"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/computer-vision","display_name":"Computer vision","score":0.8011879920959473},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.7972531318664551},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7193799614906311},{"id":"https://openalex.org/keywords/pixel","display_name":"Pixel","score":0.7192376852035522},{"id":"https://openalex.org/keywords/image-sensor","display_name":"Image sensor","score":0.6636142134666443},{"id":"https://openalex.org/keywords/biometrics","display_name":"Biometrics","score":0.6554533839225769},{"id":"https://openalex.org/keywords/fingerprint","display_name":"Fingerprint (computing)","score":0.5857746601104736},{"id":"https://openalex.org/keywords/noise","display_name":"Noise (video)","score":0.5377275347709656},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.432142972946167},{"id":"https://openalex.org/keywords/fingerprint-recognition","display_name":"Fingerprint recognition","score":0.4263852834701538},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.3464929163455963}],"concepts":[{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.8011879920959473},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7972531318664551},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7193799614906311},{"id":"https://openalex.org/C160633673","wikidata":"https://www.wikidata.org/wiki/Q355198","display_name":"Pixel","level":2,"score":0.7192376852035522},{"id":"https://openalex.org/C76935873","wikidata":"https://www.wikidata.org/wiki/Q209121","display_name":"Image sensor","level":2,"score":0.6636142134666443},{"id":"https://openalex.org/C184297639","wikidata":"https://www.wikidata.org/wiki/Q177765","display_name":"Biometrics","level":2,"score":0.6554533839225769},{"id":"https://openalex.org/C2777826928","wikidata":"https://www.wikidata.org/wiki/Q3745713","display_name":"Fingerprint (computing)","level":2,"score":0.5857746601104736},{"id":"https://openalex.org/C99498987","wikidata":"https://www.wikidata.org/wiki/Q2210247","display_name":"Noise (video)","level":3,"score":0.5377275347709656},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.432142972946167},{"id":"https://openalex.org/C168406668","wikidata":"https://www.wikidata.org/wiki/Q178022","display_name":"Fingerprint recognition","level":3,"score":0.4263852834701538},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.3464929163455963}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/btas.2016.7791195","is_oa":false,"landing_page_url":"https://doi.org/10.1109/btas.2016.7791195","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2016 IEEE 8th International Conference on Biometrics Theory, Applications and Systems (BTAS)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":24,"referenced_works":["https://openalex.org/W1512403036","https://openalex.org/W1963623641","https://openalex.org/W1985110735","https://openalex.org/W2001426616","https://openalex.org/W2003884262","https://openalex.org/W2016957240","https://openalex.org/W2027654975","https://openalex.org/W2037340447","https://openalex.org/W2038425697","https://openalex.org/W2055282708","https://openalex.org/W2110449873","https://openalex.org/W2115916845","https://openalex.org/W2118498934","https://openalex.org/W2122230135","https://openalex.org/W2124177559","https://openalex.org/W2124695272","https://openalex.org/W2129240197","https://openalex.org/W2133584444","https://openalex.org/W2147555557","https://openalex.org/W3142913228","https://openalex.org/W6650605629","https://openalex.org/W6651416709","https://openalex.org/W6677793706","https://openalex.org/W6677864325"],"related_works":["https://openalex.org/W4233349824","https://openalex.org/W3014822659","https://openalex.org/W2117826006","https://openalex.org/W4362496757","https://openalex.org/W2051501574","https://openalex.org/W2124627279","https://openalex.org/W2050967184","https://openalex.org/W2566091814","https://openalex.org/W2114937328","https://openalex.org/W4200422973"],"abstract_inverted_index":{"Image":[0],"alignment":[1,30,58],"or":[2],"registration":[3],"is":[4,50,59,85,120],"needed":[5,119],"for":[6,53,144],"many":[7,145],"tasks.":[8],"Conventional":[9],"techniques":[10],"are":[11,28,95,118],"based":[12,35],"on":[13,36],"the":[14,21,24,37,40,45,64,72,77,81,90,93,101,107,121,130,133,149],"image":[15,25],"content.":[16],"For":[17],"forensic":[18],"purposes":[19],"where":[20,114],"characteristics":[22],"of":[23,57,71,92,106,123,132,151],"sensor":[26,41,48,74,124,153],"itself":[27],"investigated,":[29],"has":[31],"to":[32,43,75],"be":[33,142],"done":[34],"pixel":[38,127],"grid":[39],"used":[42],"capture":[44],"images.":[46,78,109],"Biometric":[47],"analysis":[49],"one":[51],"example":[52],"which":[54],"this":[55],"kind":[56],"needed.":[60],"Our":[61],"method":[62],"utilises":[63],"photo":[65],"response":[66],"non":[67],"uniformity":[68],"(PRNU)":[69],"fingerprint":[70],"biometric":[73,134,152],"align":[76],"At":[79],"first":[80],"PRNU":[82],"noise":[83],"residual":[84],"extracted":[86],"and":[87],"enhanced.":[88],"Then":[89],"shifts":[91],"images":[94,117],"corrected":[96],"by":[97],"determining":[98],"peaks":[99],"in":[100,129,148],"normalised":[102],"cross":[103],"correlation":[104],"results":[105],"individual":[108],"One":[110],"possible":[111],"use":[112],"case":[113],"such":[115],"aligned":[116],"detection":[122],"ageing":[125,136],"related":[126],"defects":[128],"scope":[131],"template":[135],"phenomenon":[137],"but":[138],"our":[139],"approach":[140],"can":[141],"useful":[143],"other":[146],"tasks":[147],"field":[150],"analysis.":[154]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2021,"cited_by_count":1},{"year":2020,"cited_by_count":1},{"year":2019,"cited_by_count":1},{"year":2017,"cited_by_count":1}],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}