{"id":"https://openalex.org/W1967444466","doi":"https://doi.org/10.1109/icip.2013.6738919","title":"Image splicing detection based on noncausal Markov model","display_name":"Image splicing detection based on noncausal Markov model","publication_year":2013,"publication_date":"2013-09-01","ids":{"openalex":"https://openalex.org/W1967444466","doi":"https://doi.org/10.1109/icip.2013.6738919","mag":"1967444466"},"language":"en","primary_location":{"id":"doi:10.1109/icip.2013.6738919","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icip.2013.6738919","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2013 IEEE International Conference on Image Processing","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/A5054894664","display_name":"Xudong Zhao","orcid":"https://orcid.org/0000-0003-2272-6278"},"institutions":[{"id":"https://openalex.org/I183067930","display_name":"Shanghai Jiao Tong University","ror":"https://ror.org/0220qvk04","country_code":"CN","type":"education","lineage":["https://openalex.org/I183067930"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xudong Zhao","raw_affiliation_strings":["Department of Electronic Engineering, Shanghai Jiao Tong University, Shanghai, 200240 P.R. China","Dept of Electron. Eng., Shanghai Jiao Tong Univ., Shanghai, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Electronic Engineering, Shanghai Jiao Tong University, Shanghai, 200240 P.R. China","institution_ids":["https://openalex.org/I183067930"]},{"raw_affiliation_string":"Dept of Electron. Eng., Shanghai Jiao Tong Univ., Shanghai, China","institution_ids":["https://openalex.org/I183067930"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101717685","display_name":"Shilin Wang","orcid":"https://orcid.org/0000-0002-8214-6809"},"institutions":[{"id":"https://openalex.org/I183067930","display_name":"Shanghai Jiao Tong University","ror":"https://ror.org/0220qvk04","country_code":"CN","type":"education","lineage":["https://openalex.org/I183067930"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Shilin Wang","raw_affiliation_strings":["School of Information Security Engineering, Shanghai Jiao Tong University, Shanghai, 200240 P.R. China","[School of Information Security Engineering Shanghai Jiao Tong University, Shanghai, China]"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Information Security Engineering, Shanghai Jiao Tong University, Shanghai, 200240 P.R. China","institution_ids":["https://openalex.org/I183067930"]},{"raw_affiliation_string":"[School of Information Security Engineering Shanghai Jiao Tong University, Shanghai, China]","institution_ids":["https://openalex.org/I183067930"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100673372","display_name":"Shenghong Li","orcid":"https://orcid.org/0000-0002-0767-2307"},"institutions":[{"id":"https://openalex.org/I183067930","display_name":"Shanghai Jiao Tong University","ror":"https://ror.org/0220qvk04","country_code":"CN","type":"education","lineage":["https://openalex.org/I183067930"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Shenghong Li","raw_affiliation_strings":["Department of Electronic Engineering, Shanghai Jiao Tong University, Shanghai, 200240 P.R. China","Dept of Electron. Eng., Shanghai Jiao Tong Univ., Shanghai, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Electronic Engineering, Shanghai Jiao Tong University, Shanghai, 200240 P.R. China","institution_ids":["https://openalex.org/I183067930"]},{"raw_affiliation_string":"Dept of Electron. Eng., Shanghai Jiao Tong Univ., Shanghai, China","institution_ids":["https://openalex.org/I183067930"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100391361","display_name":"Jianhua Li","orcid":"https://orcid.org/0000-0002-6831-3973"},"institutions":[{"id":"https://openalex.org/I183067930","display_name":"Shanghai Jiao Tong University","ror":"https://ror.org/0220qvk04","country_code":"CN","type":"education","lineage":["https://openalex.org/I183067930"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jianhua Li","raw_affiliation_strings":["Department of Electronic Engineering, Shanghai Jiao Tong University, Shanghai, 200240 P.R. China","Dept of Electron. Eng., Shanghai Jiao Tong Univ., Shanghai, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Electronic Engineering, Shanghai Jiao Tong University, Shanghai, 200240 P.R. China","institution_ids":["https://openalex.org/I183067930"]},{"raw_affiliation_string":"Dept of Electron. Eng., Shanghai Jiao Tong Univ., Shanghai, China","institution_ids":["https://openalex.org/I183067930"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5057022406","display_name":"Quanqiao Yuan","orcid":null},"institutions":[{"id":"https://openalex.org/I183067930","display_name":"Shanghai Jiao Tong University","ror":"https://ror.org/0220qvk04","country_code":"CN","type":"education","lineage":["https://openalex.org/I183067930"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Quanqiao Yuan","raw_affiliation_strings":["School of Information Security Engineering, Shanghai Jiao Tong University, Shanghai, 200240 P.R. China","[School of Information Security Engineering Shanghai Jiao Tong University, Shanghai, China]"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Information Security Engineering, Shanghai Jiao Tong University, Shanghai, 200240 P.R. China","institution_ids":["https://openalex.org/I183067930"]},{"raw_affiliation_string":"[School of Information Security Engineering Shanghai Jiao Tong University, Shanghai, China]","institution_ids":["https://openalex.org/I183067930"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I183067930"],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":19,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"4462","last_page":"4466"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12357","display_name":"Digital Media Forensic Detection","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/T12357","display_name":"Digital Media Forensic Detection","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/T10388","display_name":"Advanced Steganography and Watermarking Techniques","score":0.9926999807357788,"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/T13114","display_name":"Image Processing Techniques and Applications","score":0.9911999702453613,"subfield":{"id":"https://openalex.org/subfields/2214","display_name":"Media Technology"},"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/discriminative-model","display_name":"Discriminative model","score":0.6422302722930908},{"id":"https://openalex.org/keywords/markov-chain","display_name":"Markov chain","score":0.5902284979820251},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5875340700149536},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5829339623451233},{"id":"https://openalex.org/keywords/markov-model","display_name":"Markov model","score":0.5448122620582581},{"id":"https://openalex.org/keywords/discrete-cosine-transform","display_name":"Discrete cosine transform","score":0.5406252145767212},{"id":"https://openalex.org/keywords/generalization","display_name":"Generalization","score":0.5371361970901489},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.5196203589439392},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.47973933815956116},{"id":"https://openalex.org/keywords/maximum-entropy-markov-model","display_name":"Maximum-entropy Markov model","score":0.4730079472064972},{"id":"https://openalex.org/keywords/hidden-markov-model","display_name":"Hidden Markov model","score":0.47133588790893555},{"id":"https://openalex.org/keywords/markov-process","display_name":"Markov process","score":0.46841397881507874},{"id":"https://openalex.org/keywords/domain","display_name":"Domain (mathematical analysis)","score":0.43835124373435974},{"id":"https://openalex.org/keywords/rna-splicing","display_name":"RNA splicing","score":0.42223939299583435},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.39280077815055847},{"id":"https://openalex.org/keywords/variable-order-markov-model","display_name":"Variable-order Markov model","score":0.2647275924682617},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.25139904022216797},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.12149885296821594}],"concepts":[{"id":"https://openalex.org/C97931131","wikidata":"https://www.wikidata.org/wiki/Q5282087","display_name":"Discriminative model","level":2,"score":0.6422302722930908},{"id":"https://openalex.org/C98763669","wikidata":"https://www.wikidata.org/wiki/Q176645","display_name":"Markov chain","level":2,"score":0.5902284979820251},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5875340700149536},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5829339623451233},{"id":"https://openalex.org/C163836022","wikidata":"https://www.wikidata.org/wiki/Q6771326","display_name":"Markov model","level":3,"score":0.5448122620582581},{"id":"https://openalex.org/C2221639","wikidata":"https://www.wikidata.org/wiki/Q2877","display_name":"Discrete cosine transform","level":3,"score":0.5406252145767212},{"id":"https://openalex.org/C177148314","wikidata":"https://www.wikidata.org/wiki/Q170084","display_name":"Generalization","level":2,"score":0.5371361970901489},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.5196203589439392},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.47973933815956116},{"id":"https://openalex.org/C196956702","wikidata":"https://www.wikidata.org/wiki/Q6795829","display_name":"Maximum-entropy Markov model","level":5,"score":0.4730079472064972},{"id":"https://openalex.org/C23224414","wikidata":"https://www.wikidata.org/wiki/Q176769","display_name":"Hidden Markov model","level":2,"score":0.47133588790893555},{"id":"https://openalex.org/C159886148","wikidata":"https://www.wikidata.org/wiki/Q176645","display_name":"Markov process","level":2,"score":0.46841397881507874},{"id":"https://openalex.org/C36503486","wikidata":"https://www.wikidata.org/wiki/Q11235244","display_name":"Domain (mathematical analysis)","level":2,"score":0.43835124373435974},{"id":"https://openalex.org/C54458228","wikidata":"https://www.wikidata.org/wiki/Q237218","display_name":"RNA splicing","level":4,"score":0.42223939299583435},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.39280077815055847},{"id":"https://openalex.org/C54907487","wikidata":"https://www.wikidata.org/wiki/Q7915688","display_name":"Variable-order Markov model","level":4,"score":0.2647275924682617},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.25139904022216797},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.12149885296821594},{"id":"https://openalex.org/C104317684","wikidata":"https://www.wikidata.org/wiki/Q7187","display_name":"Gene","level":2,"score":0.0},{"id":"https://openalex.org/C67705224","wikidata":"https://www.wikidata.org/wiki/Q11053","display_name":"RNA","level":3,"score":0.0},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.0},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.0},{"id":"https://openalex.org/C55493867","wikidata":"https://www.wikidata.org/wiki/Q7094","display_name":"Biochemistry","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icip.2013.6738919","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icip.2013.6738919","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2013 IEEE International Conference on Image Processing","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.7599999904632568,"display_name":"Reduced inequalities","id":"https://metadata.un.org/sdg/10"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":12,"referenced_works":["https://openalex.org/W1991430118","https://openalex.org/W2019716459","https://openalex.org/W2031466562","https://openalex.org/W2049633694","https://openalex.org/W2061395358","https://openalex.org/W2089818991","https://openalex.org/W2106663508","https://openalex.org/W2110100393","https://openalex.org/W2153635508","https://openalex.org/W3129711340","https://openalex.org/W6648332105","https://openalex.org/W6655480541"],"related_works":["https://openalex.org/W2134386692","https://openalex.org/W2379938888","https://openalex.org/W1510894296","https://openalex.org/W2116722627","https://openalex.org/W1977445474","https://openalex.org/W4233405330","https://openalex.org/W2194396582","https://openalex.org/W2082284720","https://openalex.org/W2566202039","https://openalex.org/W2799426416"],"abstract_inverted_index":{"In":[0],"this":[1],"paper,":[2],"a":[3,32],"noncausal":[4,34],"Markov":[5,18],"model":[6,19,48,51,74],"is":[7],"proposed":[8,25,69,94],"for":[9,58],"digital":[10],"image":[11,21],"splicing":[12,22],"detection.":[13],"Different":[14],"from":[15],"the":[16,24,38,44,47,50,63,68,73,76,93,99],"traditional":[17],"in":[20,75],"detection,":[23],"approach":[26,95],"models":[27],"an":[28],"observation":[29],"array":[30],"as":[31,55],"2-D":[33],"signal":[35],"and":[36,49,65,80,87],"captures":[37],"underlying":[39],"statistical":[40],"characteristics.":[41],"We":[42],"give":[43],"solutions":[45],"to":[46],"parameters":[52],"are":[53],"treated":[54],"discriminative":[56],"features":[57],"classification":[59],"(detection).":[60],"To":[61],"evaluate":[62],"generalization":[64],"effectiveness":[66],"of":[67,98],"method,":[70],"we":[71],"apply":[72],"block":[77],"DCT":[78],"domain":[79,85],"discrete":[81],"Meyer":[82],"wavelet":[83],"transform":[84],"respectively":[86],"experimental":[88],"results":[89],"have":[90],"shown":[91],"that":[92],"outperforms":[96],"most":[97],"state-of-the-art":[100],"methods.":[101]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2022,"cited_by_count":2},{"year":2021,"cited_by_count":2},{"year":2020,"cited_by_count":2},{"year":2019,"cited_by_count":1},{"year":2018,"cited_by_count":1},{"year":2017,"cited_by_count":2},{"year":2015,"cited_by_count":4},{"year":2014,"cited_by_count":4}],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}