{"id":"https://openalex.org/W2118090703","doi":"https://doi.org/10.1109/icpr.2008.4761645","title":"A machine learning based scheme for double JPEG compression detection","display_name":"A machine learning based scheme for double JPEG compression detection","publication_year":2008,"publication_date":"2008-12-01","ids":{"openalex":"https://openalex.org/W2118090703","doi":"https://doi.org/10.1109/icpr.2008.4761645","mag":"2118090703"},"language":"en","primary_location":{"id":"doi:10.1109/icpr.2008.4761645","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icpr.2008.4761645","pdf_url":null,"source":{"id":"https://openalex.org/S4393916651","display_name":"Proceedings - International Conference on Pattern Recognition/Proceedings/International Conference on Pattern Recognition","issn_l":"1041-3278","issn":["1041-3278","1051-4651"],"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2008 19th International Conference on Pattern Recognition","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/A5100667062","display_name":"Chunhua Chen","orcid":"https://orcid.org/0000-0002-4087-5309"},"institutions":[{"id":"https://openalex.org/I118118575","display_name":"New Jersey Institute of Technology","ror":"https://ror.org/05e74xb87","country_code":"US","type":"education","lineage":["https://openalex.org/I118118575"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Chunhua Chen","raw_affiliation_strings":["New Jersey Institute of Technology, Newark, NJ, USA","[New Jersey Institute of Technology, Newark, NJ]"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"New Jersey Institute of Technology, Newark, NJ, USA","institution_ids":["https://openalex.org/I118118575"]},{"raw_affiliation_string":"[New Jersey Institute of Technology, Newark, NJ]","institution_ids":["https://openalex.org/I118118575"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5112253415","display_name":"Yun Q. Shi","orcid":"https://orcid.org/0009-0007-4038-0430"},"institutions":[{"id":"https://openalex.org/I118118575","display_name":"New Jersey Institute of Technology","ror":"https://ror.org/05e74xb87","country_code":"US","type":"education","lineage":["https://openalex.org/I118118575"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Yun Q. Shi","raw_affiliation_strings":["New Jersey Institute of Technology, Newark, NJ, USA","[New Jersey Institute of Technology, Newark, NJ]"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"New Jersey Institute of Technology, Newark, NJ, USA","institution_ids":["https://openalex.org/I118118575"]},{"raw_affiliation_string":"[New Jersey Institute of Technology, Newark, NJ]","institution_ids":["https://openalex.org/I118118575"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100755437","display_name":"Wei Su","orcid":"https://orcid.org/0000-0003-0952-0398"},"institutions":[{"id":"https://openalex.org/I118118575","display_name":"New Jersey Institute of Technology","ror":"https://ror.org/05e74xb87","country_code":"US","type":"education","lineage":["https://openalex.org/I118118575"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Wei Su","raw_affiliation_strings":["New Jersey Institute of Technology, Newark, NJ, USA","[New Jersey Institute of Technology, Newark, NJ]"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"New Jersey Institute of Technology, Newark, NJ, USA","institution_ids":["https://openalex.org/I118118575"]},{"raw_affiliation_string":"[New Jersey Institute of Technology, Newark, NJ]","institution_ids":["https://openalex.org/I118118575"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I118118575"],"apc_list":null,"apc_paid":null,"fwci":6.0485,"has_fulltext":false,"cited_by_count":111,"citation_normalized_percentile":{"value":0.97808658,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":90,"max":99},"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"4"},"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/T10388","display_name":"Advanced Steganography and Watermarking Techniques","score":0.9936000108718872,"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/T10775","display_name":"Generative Adversarial Networks and Image Synthesis","score":0.9919000267982483,"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/jpeg","display_name":"JPEG","score":0.8788168430328369},{"id":"https://openalex.org/keywords/lossless-jpeg","display_name":"Lossless JPEG","score":0.8698542714118958},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6541524529457092},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6447405815124512},{"id":"https://openalex.org/keywords/thresholding","display_name":"Thresholding","score":0.5961176753044128},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4632412791252136},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.44869354367256165},{"id":"https://openalex.org/keywords/jpeg-2000","display_name":"JPEG 2000","score":0.4388030469417572},{"id":"https://openalex.org/keywords/compression-artifact","display_name":"Compression artifact","score":0.43030446767807007},{"id":"https://openalex.org/keywords/transform-coding","display_name":"Transform coding","score":0.4189777970314026},{"id":"https://openalex.org/keywords/data-compression","display_name":"Data compression","score":0.36866825819015503},{"id":"https://openalex.org/keywords/image-compression","display_name":"Image compression","score":0.32254183292388916},{"id":"https://openalex.org/keywords/discrete-cosine-transform","display_name":"Discrete cosine transform","score":0.30504110455513},{"id":"https://openalex.org/keywords/image-processing","display_name":"Image processing","score":0.2964167296886444},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.11318936944007874}],"concepts":[{"id":"https://openalex.org/C198751489","wikidata":"https://www.wikidata.org/wiki/Q2195","display_name":"JPEG","level":3,"score":0.8788168430328369},{"id":"https://openalex.org/C8384606","wikidata":"https://www.wikidata.org/wiki/Q2190356","display_name":"Lossless JPEG","level":5,"score":0.8698542714118958},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6541524529457092},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6447405815124512},{"id":"https://openalex.org/C191178318","wikidata":"https://www.wikidata.org/wiki/Q2256906","display_name":"Thresholding","level":3,"score":0.5961176753044128},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4632412791252136},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.44869354367256165},{"id":"https://openalex.org/C69216139","wikidata":"https://www.wikidata.org/wiki/Q931783","display_name":"JPEG 2000","level":5,"score":0.4388030469417572},{"id":"https://openalex.org/C57654395","wikidata":"https://www.wikidata.org/wiki/Q1097775","display_name":"Compression artifact","level":5,"score":0.43030446767807007},{"id":"https://openalex.org/C169805256","wikidata":"https://www.wikidata.org/wiki/Q1361381","display_name":"Transform coding","level":4,"score":0.4189777970314026},{"id":"https://openalex.org/C78548338","wikidata":"https://www.wikidata.org/wiki/Q2493","display_name":"Data compression","level":2,"score":0.36866825819015503},{"id":"https://openalex.org/C13481523","wikidata":"https://www.wikidata.org/wiki/Q412438","display_name":"Image compression","level":4,"score":0.32254183292388916},{"id":"https://openalex.org/C2221639","wikidata":"https://www.wikidata.org/wiki/Q2877","display_name":"Discrete cosine transform","level":3,"score":0.30504110455513},{"id":"https://openalex.org/C9417928","wikidata":"https://www.wikidata.org/wiki/Q1070689","display_name":"Image processing","level":3,"score":0.2964167296886444},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.11318936944007874}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/icpr.2008.4761645","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icpr.2008.4761645","pdf_url":null,"source":{"id":"https://openalex.org/S4393916651","display_name":"Proceedings - International Conference on Pattern Recognition/Proceedings/International Conference on Pattern Recognition","issn_l":"1041-3278","issn":["1041-3278","1051-4651"],"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2008 19th International Conference on Pattern Recognition","raw_type":"proceedings-article"},{"id":"pmh:oai:CiteSeerX.psu:10.1.1.214.3894","is_oa":false,"landing_page_url":"http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.214.3894","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"http://figment.cse.usf.edu/~sfefilat/data/papers/TuBCT9.42.pdf","raw_type":"text"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":9,"referenced_works":["https://openalex.org/W200526583","https://openalex.org/W2061310904","https://openalex.org/W2070040249","https://openalex.org/W2108360315","https://openalex.org/W2153635508","https://openalex.org/W3120421331","https://openalex.org/W4241879879","https://openalex.org/W6608096262","https://openalex.org/W6668164699"],"related_works":["https://openalex.org/W3190486427","https://openalex.org/W4243959093","https://openalex.org/W1998280942","https://openalex.org/W2441603424","https://openalex.org/W1992410481","https://openalex.org/W2145138541","https://openalex.org/W3137515556","https://openalex.org/W1836399137","https://openalex.org/W2545896937","https://openalex.org/W2111280862"],"abstract_inverted_index":{"Double":[0],"JPEG":[1,24,29,39,46,60,114],"compression":[2,61,115],"detection":[3],"is":[4,66,86,121],"of":[5,38,43,92,105],"significance":[6],"in":[7],"digital":[8],"forensics.":[9],"We":[10],"propose":[11],"an":[12],"effective":[13],"machine":[14,120],"learning":[15],"based":[16],"scheme":[17,132],"to":[18,57,69,76,88],"distinguish":[19],"between":[20,35],"double":[21,59,113],"and":[22,48],"single":[23],"compressed":[25],"images.":[26],"Firstly,":[27],"difference":[28,34,71],"2D":[30,41],"arrays,":[31],"i.e.,":[32],"the":[33,36,78,90,93,99,124,135],"magnitude":[37],"coefficient":[40],"array":[42],"a":[44,83],"given":[45],"image":[47],"its":[49],"shifted":[50],"versions":[51],"along":[52],"various":[53],"directions,":[54],"are":[55,108],"used":[56,87],"enhance":[58],"artifacts.":[62],"Markov":[63,100],"random":[64,101],"process":[65],"then":[67],"applied":[68],"modeling":[70],"2-D":[72],"arrays":[73],"so":[74],"as":[75,110,123],"utilize":[77],"second-order":[79],"statistics.":[80],"In":[81],"addition,":[82],"thresholding":[84],"technique":[85],"reduce":[89],"size":[91],"transition":[94],"probability":[95],"matrices,":[96],"which":[97],"characterize":[98],"processes.":[102],"All":[103],"elements":[104],"these":[106],"matrices":[107],"collected":[109],"features":[111],"for":[112],"detection.":[116],"The":[117],"support":[118],"vector":[119],"employed":[122],"classifier.":[125],"Experiments":[126],"have":[127],"demonstrated":[128],"that":[129],"our":[130],"proposed":[131],"has":[133],"outperformed":[134],"prior":[136],"arts.":[137]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":7},{"year":2024,"cited_by_count":4},{"year":2023,"cited_by_count":4},{"year":2022,"cited_by_count":1},{"year":2021,"cited_by_count":5},{"year":2020,"cited_by_count":7},{"year":2019,"cited_by_count":6},{"year":2018,"cited_by_count":11},{"year":2017,"cited_by_count":8},{"year":2016,"cited_by_count":7},{"year":2015,"cited_by_count":8},{"year":2014,"cited_by_count":10},{"year":2013,"cited_by_count":10},{"year":2012,"cited_by_count":8}],"updated_date":"2026-06-26T08:34:08.712188","created_date":"2025-10-10T00:00:00"}