{"id":"https://openalex.org/W3155274151","doi":"https://doi.org/10.1145/3446999.3447024","title":"Research on Restoration Algorithm of Halftone Anti-counterfeiting Images","display_name":"Research on Restoration Algorithm of Halftone Anti-counterfeiting Images","publication_year":2020,"publication_date":"2020-12-25","ids":{"openalex":"https://openalex.org/W3155274151","doi":"https://doi.org/10.1145/3446999.3447024","mag":"3155274151"},"language":"en","primary_location":{"id":"doi:10.1145/3446999.3447024","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3446999.3447024","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2020 8th International Conference on Information Technology: IoT and Smart City","raw_type":"proceedings-article"},"type":"conference-paper","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/A5086231269","display_name":"Yumeng Zhen","orcid":null},"institutions":[{"id":"https://openalex.org/I4210135483","display_name":"Beijing Institute of Graphic Communication","ror":"https://ror.org/03yg3v757","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210135483"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yumeng Zhen","raw_affiliation_strings":["Beijing Key Laboratory of Signal and Information Processing for High-end Printing Equipment Beijing Institute of Graphic Communication, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Beijing Key Laboratory of Signal and Information Processing for High-end Printing Equipment Beijing Institute of Graphic Communication, China","institution_ids":["https://openalex.org/I4210135483"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5106405073","display_name":"Peng Cao","orcid":"https://orcid.org/0000-0002-9629-1273"},"institutions":[{"id":"https://openalex.org/I4210135483","display_name":"Beijing Institute of Graphic Communication","ror":"https://ror.org/03yg3v757","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210135483"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Peng Cao","raw_affiliation_strings":["Beijing Key Laboratory of Signal and Information Processing for High-end Printing Equipment Beijing Institute of Graphic Communication, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Beijing Key Laboratory of Signal and Information Processing for High-end Printing Equipment Beijing Institute of Graphic Communication, China","institution_ids":["https://openalex.org/I4210135483"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I4210135483"],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"133","last_page":"137"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12111","display_name":"Industrial Vision Systems and Defect Detection","score":0.8299000263214111,"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"}},"topics":[{"id":"https://openalex.org/T12111","display_name":"Industrial Vision Systems and Defect Detection","score":0.8299000263214111,"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/T14257","display_name":"Advanced Measurement and Detection Methods","score":0.7512999773025513,"subfield":{"id":"https://openalex.org/subfields/2208","display_name":"Electrical and Electronic Engineering"},"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/halftone","display_name":"Halftone","score":0.971072793006897},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7331328988075256},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.687700629234314},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6005649566650391},{"id":"https://openalex.org/keywords/code","display_name":"Code (set theory)","score":0.588559627532959},{"id":"https://openalex.org/keywords/image-restoration","display_name":"Image restoration","score":0.5831512212753296},{"id":"https://openalex.org/keywords/pixel","display_name":"Pixel","score":0.532200038433075},{"id":"https://openalex.org/keywords/mobile-phone","display_name":"Mobile phone","score":0.5309735536575317},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.46764183044433594},{"id":"https://openalex.org/keywords/noise","display_name":"Noise (video)","score":0.43040451407432556},{"id":"https://openalex.org/keywords/image-quality","display_name":"Image quality","score":0.414654403924942},{"id":"https://openalex.org/keywords/image-processing","display_name":"Image processing","score":0.30654510855674744},{"id":"https://openalex.org/keywords/telecommunications","display_name":"Telecommunications","score":0.12233677506446838}],"concepts":[{"id":"https://openalex.org/C2777635815","wikidata":"https://www.wikidata.org/wiki/Q1110021","display_name":"Halftone","level":3,"score":0.971072793006897},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7331328988075256},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.687700629234314},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6005649566650391},{"id":"https://openalex.org/C2776760102","wikidata":"https://www.wikidata.org/wiki/Q5139990","display_name":"Code (set theory)","level":3,"score":0.588559627532959},{"id":"https://openalex.org/C106430172","wikidata":"https://www.wikidata.org/wiki/Q6002272","display_name":"Image restoration","level":4,"score":0.5831512212753296},{"id":"https://openalex.org/C160633673","wikidata":"https://www.wikidata.org/wiki/Q355198","display_name":"Pixel","level":2,"score":0.532200038433075},{"id":"https://openalex.org/C2777421447","wikidata":"https://www.wikidata.org/wiki/Q17517","display_name":"Mobile phone","level":2,"score":0.5309735536575317},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.46764183044433594},{"id":"https://openalex.org/C99498987","wikidata":"https://www.wikidata.org/wiki/Q2210247","display_name":"Noise (video)","level":3,"score":0.43040451407432556},{"id":"https://openalex.org/C55020928","wikidata":"https://www.wikidata.org/wiki/Q3813865","display_name":"Image quality","level":3,"score":0.414654403924942},{"id":"https://openalex.org/C9417928","wikidata":"https://www.wikidata.org/wiki/Q1070689","display_name":"Image processing","level":3,"score":0.30654510855674744},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.12233677506446838},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"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:10.1145/3446999.3447024","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3446999.3447024","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2020 8th International Conference on Information Technology: IoT and Smart City","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Sustainable cities and communities","id":"https://metadata.un.org/sdg/11","score":0.6499999761581421}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":1,"referenced_works":["https://openalex.org/W4236060337"],"related_works":["https://openalex.org/W4251316475","https://openalex.org/W387710534","https://openalex.org/W1990318175","https://openalex.org/W608034372","https://openalex.org/W4378219109","https://openalex.org/W2049375232","https://openalex.org/W2383705254","https://openalex.org/W2063075950","https://openalex.org/W4378446391","https://openalex.org/W2801208768"],"abstract_inverted_index":{"The":[0],"anti-counterfeiting":[1,23,40,148],"information":[2,20,41,144],"is":[3,24,49],"implanted":[4],"into":[5],"the":[6,27,34,38,68,76,80,92,99,104,108,113,124,137],"QR":[7,46,70],"Code":[8,71],"with":[9,129],"tiny":[10],"pixels":[11],"as":[12,57],"single":[13],"halftone":[14,147],"dot.":[15],"This":[16],"method":[17,96,133],"to":[18,51,85,97,112],"realize":[19],"hiding":[21],"and":[22,61,74,107,121],"one":[25],"of":[26,42,45,63,79,115,139,142],"research":[28],"hotspots":[29],"in":[30,145],"this":[31,43,89,132],"field.":[32],"When":[33],"mobile":[35,58],"phone":[36,59],"identifies":[37],"micro-scale":[39],"type":[44],"Code,":[47],"it":[48],"easy":[50],"be":[52],"affected":[53],"by":[54],"factors":[55],"such":[56,146],"shake":[60],"out":[62],"focus,":[64],"which":[65],"will":[66],"make":[67],"scanned":[69],"image":[72,106,110,126],"blurred":[73,105,125,149],"affect":[75],"effective":[77],"identifying":[78],"carried":[81],"information.":[82],"In":[83],"order":[84],"obtain":[86],"higher-quality":[87],"images,":[88,120],"paper":[90],"uses":[91],"BP":[93],"neural":[94],"network":[95],"calculate":[98],"optimal":[100],"mapping":[101],"model":[102],"between":[103],"original":[109],"according":[111],"characteristics":[114],"hidden":[116],"halftoning":[117],"pseudo-random":[118],"noise":[119],"then":[122],"realizes":[123],"restoration.":[127],"Compared":[128],"traditional":[130],"methods,":[131],"can":[134],"effectively":[135],"solve":[136],"problem":[138],"high-quality":[140],"restoration":[141],"microstructure":[143],"images.":[150]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2022,"cited_by_count":1}],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}
