{"id":"https://openalex.org/W2040819105","doi":"https://doi.org/10.1109/tifs.2014.2355912","title":"A Novel Gain Invariant Quantization-Based Watermarking Approach","display_name":"A Novel Gain Invariant Quantization-Based Watermarking Approach","publication_year":2014,"publication_date":"2014-09-10","ids":{"openalex":"https://openalex.org/W2040819105","doi":"https://doi.org/10.1109/tifs.2014.2355912","mag":"2040819105"},"language":"en","primary_location":{"id":"doi:10.1109/tifs.2014.2355912","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tifs.2014.2355912","pdf_url":null,"source":{"id":"https://openalex.org/S61310614","display_name":"IEEE Transactions on Information Forensics and Security","issn_l":"1556-6013","issn":["1556-6013","1556-6021"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Information Forensics and Security","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/A5006363557","display_name":"Mohsen Zareian","orcid":null},"institutions":[{"id":"https://openalex.org/I158248296","display_name":"Amirkabir University of Technology","ror":"https://ror.org/04gzbav43","country_code":"IR","type":"education","lineage":["https://openalex.org/I158248296"]}],"countries":["IR"],"is_corresponding":true,"raw_author_name":"Mohsen Zareian","raw_affiliation_strings":["Department of Electrical Engineering, Amirkabir University of Technology, Tehran, Iran","Department of Electrical Engineering, Amirkabir University of Technology , Tehran, Iran#TAB#"],"affiliations":[{"raw_affiliation_string":"Department of Electrical Engineering, Amirkabir University of Technology, Tehran, Iran","institution_ids":["https://openalex.org/I158248296"]},{"raw_affiliation_string":"Department of Electrical Engineering, Amirkabir University of Technology , Tehran, Iran#TAB#","institution_ids":["https://openalex.org/I158248296"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5013402157","display_name":"Hamid Reza Tohidypour","orcid":"https://orcid.org/0000-0003-0469-8410"},"institutions":[{"id":"https://openalex.org/I141945490","display_name":"University of British Columbia","ror":"https://ror.org/03rmrcq20","country_code":"CA","type":"education","lineage":["https://openalex.org/I141945490"]}],"countries":["CA"],"is_corresponding":false,"raw_author_name":"Hamid Reza Tohidypour","raw_affiliation_strings":["Department of Electrical and Computer Engineering, University of British Columbia, Vancouver, BC, Canada","Department of Electrical and Computer Engineering University of British Columbia  Vancouver BC Canada"],"affiliations":[{"raw_affiliation_string":"Department of Electrical and Computer Engineering, University of British Columbia, Vancouver, BC, Canada","institution_ids":["https://openalex.org/I141945490"]},{"raw_affiliation_string":"Department of Electrical and Computer Engineering University of British Columbia  Vancouver BC Canada","institution_ids":["https://openalex.org/I141945490"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5006363557"],"corresponding_institution_ids":["https://openalex.org/I158248296"],"apc_list":null,"apc_paid":null,"fwci":1.951,"has_fulltext":false,"cited_by_count":27,"citation_normalized_percentile":{"value":0.88973291,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":91,"max":99},"biblio":{"volume":"9","issue":"11","first_page":"1804","last_page":"1813"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10388","display_name":"Advanced Steganography and Watermarking Techniques","score":1.0,"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/T10388","display_name":"Advanced Steganography and Watermarking Techniques","score":1.0,"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/T11017","display_name":"Chaos-based Image/Signal Encryption","score":0.9991999864578247,"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/T12357","display_name":"Digital Media Forensic Detection","score":0.9966999888420105,"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/digital-watermarking","display_name":"Digital watermarking","score":0.7262313365936279},{"id":"https://openalex.org/keywords/watermark","display_name":"Watermark","score":0.6155273914337158},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5426040887832642},{"id":"https://openalex.org/keywords/quantization","display_name":"Quantization (signal processing)","score":0.5302982330322266},{"id":"https://openalex.org/keywords/embedding","display_name":"Embedding","score":0.5294610857963562},{"id":"https://openalex.org/keywords/decoding-methods","display_name":"Decoding methods","score":0.5073563456535339},{"id":"https://openalex.org/keywords/invariant","display_name":"Invariant (physics)","score":0.506618857383728},{"id":"https://openalex.org/keywords/euclidean-distance","display_name":"Euclidean distance","score":0.46359461545944214},{"id":"https://openalex.org/keywords/norm","display_name":"Norm (philosophy)","score":0.4630124568939209},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.44836825132369995},{"id":"https://openalex.org/keywords/exponential-function","display_name":"Exponential function","score":0.41949376463890076},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.3806885778903961},{"id":"https://openalex.org/keywords/discrete-mathematics","display_name":"Discrete mathematics","score":0.33685940504074097},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.3061489164829254},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.2953224182128906},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.11544901132583618},{"id":"https://openalex.org/keywords/mathematical-analysis","display_name":"Mathematical analysis","score":0.0787610113620758}],"concepts":[{"id":"https://openalex.org/C150817343","wikidata":"https://www.wikidata.org/wiki/Q875932","display_name":"Digital watermarking","level":3,"score":0.7262313365936279},{"id":"https://openalex.org/C164112704","wikidata":"https://www.wikidata.org/wiki/Q7974348","display_name":"Watermark","level":3,"score":0.6155273914337158},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5426040887832642},{"id":"https://openalex.org/C28855332","wikidata":"https://www.wikidata.org/wiki/Q198099","display_name":"Quantization (signal processing)","level":2,"score":0.5302982330322266},{"id":"https://openalex.org/C41608201","wikidata":"https://www.wikidata.org/wiki/Q980509","display_name":"Embedding","level":2,"score":0.5294610857963562},{"id":"https://openalex.org/C57273362","wikidata":"https://www.wikidata.org/wiki/Q576722","display_name":"Decoding methods","level":2,"score":0.5073563456535339},{"id":"https://openalex.org/C190470478","wikidata":"https://www.wikidata.org/wiki/Q2370229","display_name":"Invariant (physics)","level":2,"score":0.506618857383728},{"id":"https://openalex.org/C120174047","wikidata":"https://www.wikidata.org/wiki/Q847073","display_name":"Euclidean distance","level":2,"score":0.46359461545944214},{"id":"https://openalex.org/C191795146","wikidata":"https://www.wikidata.org/wiki/Q3878446","display_name":"Norm (philosophy)","level":2,"score":0.4630124568939209},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.44836825132369995},{"id":"https://openalex.org/C151376022","wikidata":"https://www.wikidata.org/wiki/Q168698","display_name":"Exponential function","level":2,"score":0.41949376463890076},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.3806885778903961},{"id":"https://openalex.org/C118615104","wikidata":"https://www.wikidata.org/wiki/Q121416","display_name":"Discrete mathematics","level":1,"score":0.33685940504074097},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3061489164829254},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.2953224182128906},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.11544901132583618},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.0787610113620758},{"id":"https://openalex.org/C37914503","wikidata":"https://www.wikidata.org/wiki/Q156495","display_name":"Mathematical physics","level":1,"score":0.0},{"id":"https://openalex.org/C17744445","wikidata":"https://www.wikidata.org/wiki/Q36442","display_name":"Political science","level":0,"score":0.0},{"id":"https://openalex.org/C199539241","wikidata":"https://www.wikidata.org/wiki/Q7748","display_name":"Law","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tifs.2014.2355912","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tifs.2014.2355912","pdf_url":null,"source":{"id":"https://openalex.org/S61310614","display_name":"IEEE Transactions on Information Forensics and Security","issn_l":"1556-6013","issn":["1556-6013","1556-6021"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Information Forensics and Security","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/6","display_name":"Clean water and sanitation","score":0.44999998807907104}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":22,"referenced_works":["https://openalex.org/W1523514584","https://openalex.org/W1987406538","https://openalex.org/W2025538567","https://openalex.org/W2099139965","https://openalex.org/W2107465879","https://openalex.org/W2111233756","https://openalex.org/W2111316066","https://openalex.org/W2116467012","https://openalex.org/W2123865683","https://openalex.org/W2126660587","https://openalex.org/W2128124698","https://openalex.org/W2129353155","https://openalex.org/W2133665775","https://openalex.org/W2136506345","https://openalex.org/W2140129132","https://openalex.org/W2140432907","https://openalex.org/W2159528343","https://openalex.org/W2164978881","https://openalex.org/W2166282963","https://openalex.org/W2170151472","https://openalex.org/W3119264854","https://openalex.org/W4239883254"],"related_works":["https://openalex.org/W2137394636","https://openalex.org/W2358993821","https://openalex.org/W1516446231","https://openalex.org/W2098152888","https://openalex.org/W1559740347","https://openalex.org/W2040356834","https://openalex.org/W2385289568","https://openalex.org/W2381486749","https://openalex.org/W1514507288","https://openalex.org/W2183032046"],"abstract_inverted_index":{"This":[0],"paper":[1],"presents":[2],"a":[3],"novel":[4],"quantization-based":[5],"information":[6],"hiding":[7],"approach,":[8],"which":[9],"is":[10,23,38,62,79,111],"invariant":[11],"to":[12,70,81],"gain":[13],"attack.":[14],"In":[15],"the":[16,19,47,50,66,71,76,104,116,122,125,134],"presented":[17],"scheme,":[18],"host":[20],"signal":[21],"vector":[22,37],"first":[24],"divided":[25],"into":[26],"two":[27],"parts,":[28],"then":[29],"l":[30,51,105],"<sub":[31,52,106],"xmlns:mml=\"http://www.w3.org/1998/Math/MathML\"":[32,53,107],"xmlns:xlink=\"http://www.w3.org/1999/xlink\">p</sub>":[33,54,108],"-norm":[34,55,109],"of":[35,49,56,73,124],"each":[36,57],"calculated.":[39],"The":[40,59,84,100],"watermark":[41],"bits":[42],"are":[43,91],"embedded":[44],"by":[45,95],"quantizing":[46],"ratio":[48],"part.":[58],"decoding":[60],"scheme":[61],"performed":[63],"blindly":[64],"using":[65],"Euclidean":[67],"distance.":[68],"Due":[69],"use":[72],"division":[74],"function,":[75],"proposed":[77,126],"method":[78],"robust":[80],"scaling":[82],"attacks.":[83],"analytical":[85],"error":[86,117],"probability":[87],"and":[88,93],"embedding":[89],"distortion":[90],"derived":[92],"assessed":[94],"simulations":[96],"on":[97,114],"artificial":[98],"signals.":[99],"optimum":[101],"parameter":[102],"in":[103,131],"function":[110],"obtained":[112],"based":[113],"minimizing":[115],"probability.":[118],"Experimental":[119],"results":[120],"confirm":[121],"superiority":[123],"technique":[127],"against":[128],"common":[129],"attacks":[130],"comparison":[132],"with":[133],"existing":[135],"state-of-the-art":[136],"methods.":[137]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2021,"cited_by_count":3},{"year":2020,"cited_by_count":2},{"year":2019,"cited_by_count":6},{"year":2018,"cited_by_count":7},{"year":2017,"cited_by_count":3},{"year":2016,"cited_by_count":3},{"year":2015,"cited_by_count":2}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
