{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,10]],"date-time":"2026-07-10T23:20:42Z","timestamp":1783725642683,"version":"3.55.0"},"reference-count":34,"publisher":"Springer Science and Business Media LLC","issue":"12","license":[{"start":{"date-parts":[[2022,10,12]],"date-time":"2022-10-12T00:00:00Z","timestamp":1665532800000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2022,10,12]],"date-time":"2022-10-12T00:00:00Z","timestamp":1665532800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Multimed Tools Appl"],"published-print":{"date-parts":[[2023,5]]},"DOI":"10.1007\/s11042-022-14016-2","type":"journal-article","created":{"date-parts":[[2022,10,12]],"date-time":"2022-10-12T02:02:17Z","timestamp":1665540137000},"page":"17741-17768","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":28,"title":["A deep learning framework for copy-move forgery detection in digital images"],"prefix":"10.1007","volume":"82","author":[{"given":"Navneet","family":"Kaur","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Neeru","family":"Jindal","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Kulbir","family":"Singh","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","published-online":{"date-parts":[[2022,10,12]]},"reference":[{"key":"14016_CR1","doi-asserted-by":"publisher","first-page":"259","DOI":"10.1016\/j.jnca.2016.09.008","volume":"75","author":"NB Abd Warif","year":"2016","unstructured":"Abd Warif NB, Wahab AW, Idris MY, Ramli R, Salleh R, Shamshirband S, Choo KK (2016) Copy-move forgery detection: survey, challenges and future directions. J Netw Comput Appl 75:259\u2013278","journal-title":"J Netw Comput Appl"},{"issue":"10","key":"14016_CR2","doi-asserted-by":"publisher","first-page":"1280","DOI":"10.3390\/sym11101280","volume":"11","author":"Y Abdalla","year":"2019","unstructured":"Abdalla Y, Iqbal MT, Shehata M (2019) Convolutional neural network for copy-move forgery detection. Symmetry 11(10):1280","journal-title":"Symmetry"},{"key":"14016_CR3","doi-asserted-by":"crossref","unstructured":"Abidin AB, Majid HB, Samah AB, Hashim HB (2019) Copy-move image forgery detection using deep learning methods: a review. In 6th international conference on research and innovation in information systems (ICRIIS), pp. 1-6, IEEE","DOI":"10.1109\/ICRIIS48246.2019.9073569"},{"key":"14016_CR4","doi-asserted-by":"crossref","unstructured":"Agarwal R, Verma OP (2020) An efficient copy move forgery detection using deep learning feature extraction and matching algorithm. Multimed Tools Appl 79:7355\u20137376","DOI":"10.1007\/s11042-019-08495-z"},{"key":"14016_CR5","doi-asserted-by":"crossref","unstructured":"Al_Azrak FM, Sedik A, Dessowky MI, El Banby GM, Khalaf AA, Elkorany AS, El-Samie FEA (2020) An efficient method for image forgery detection based on trigonometric transforms and deep learning. Multimed Tools Appl 79(25\u201326):18221\u201318243","DOI":"10.1007\/s11042-019-08162-3"},{"key":"14016_CR6","doi-asserted-by":"crossref","unstructured":"Amerini I, Ballan L, Caldelli R, Del Bimbo A, Serra G (2011) A sift-based forensic method for copy\u2013move attack detection and transformation recovery. IEEE Trans Inf Forensics Secur 6(3):1099\u20131110","DOI":"10.1109\/TIFS.2011.2129512"},{"issue":"6","key":"14016_CR7","first-page":"659","volume":"28","author":"I Amerini","year":"2013","unstructured":"Amerini I, Ballan L, Caldelli R, Del Bimbo A, Del Tongo L, Serra G (2013) Copy-move forgery detection and localization by means of robust clustering with J-linkage. Signal process. Image Commun 28(6):659\u2013669","journal-title":"Image Commun"},{"key":"14016_CR8","doi-asserted-by":"crossref","unstructured":"Bravo-Solorio S, Nandi AK (2011) Exposing duplicated regions affected by reflection, rotation and scaling. In: IEEE international conference on acoustics, speech and signal processing (ICASSP). IEEE, pp\u00a01880\u20131883","DOI":"10.1109\/ICASSP.2011.5946873"},{"key":"14016_CR9","doi-asserted-by":"publisher","first-page":"36863","DOI":"10.1109\/ACCESS.2020.2974804","volume":"8","author":"H Chen","year":"2020","unstructured":"Chen H, Yang X, Lyu Y (2020) Copy-move forgery detection based on keypoint clustering and similar neighborhood search algorithm. IEEE Access 8:36863\u201336875","journal-title":"IEEE Access"},{"issue":"6","key":"14016_CR10","doi-asserted-by":"publisher","first-page":"1841","DOI":"10.1109\/TIFS.2012.2218597","volume":"7","author":"V Christlein","year":"2012","unstructured":"Christlein V, Riess C, Jordan J, Riess C, Angelopoulou E (2012) An evaluation of popular copy-move forgery detection approaches. IEEE Trans Inf Forensics Secur 7(6):1841\u20131854","journal-title":"IEEE Trans Inf Forensics Secur"},{"issue":"11","key":"14016_CR11","doi-asserted-by":"publisher","first-page":"2284","DOI":"10.1109\/TIFS.2015.2455334","volume":"10","author":"D Cozzolino","year":"2015","unstructured":"Cozzolino D, Poggi G, Verdoliva L (2015) Efficient dense-field copy\u2013move forgery detection. IEEE Trans Inf Forensics Secur 10(11):2284\u20132297","journal-title":"IEEE Trans Inf Forensics Secur"},{"issue":"11","key":"14016_CR12","doi-asserted-by":"publisher","first-page":"15353","DOI":"10.1007\/s11042-018-6891-7","volume":"78","author":"MA Elaskily","year":"2019","unstructured":"Elaskily MA, Elnemr HA, Dessouky MM, Faragallah OS (2019) Two stages object recognition based copy-move forgery detection algorithm. Multimed Tools Appl 78(11):15353\u201315373","journal-title":"Multimed Tools Appl"},{"key":"14016_CR13","first-page":"1","volume":"2020","author":"N Goel","year":"2020","unstructured":"Goel N, Kaur S, Bala R (2020) Dual branch convolutional neural network for copy move forgery detection. IET Image Process 2020:1\u201310","journal-title":"IET Image Process"},{"key":"14016_CR14","doi-asserted-by":"crossref","unstructured":"Hegazi A, Taha A, Selim MM (2021) An improved copy-move forgery detection based on density-based clustering and guaranteed outlier removal. J King Saud Univ Comput Inf Sci 33(9):1055\u20131063","DOI":"10.1016\/j.jksuci.2019.07.007"},{"issue":"43","key":"14016_CR15","doi-asserted-by":"publisher","first-page":"32037","DOI":"10.1007\/s11042-020-09275-w","volume":"79","author":"N Kaur","year":"2020","unstructured":"Kaur N, Jindal N, Singh K (2020) A passive approach for the detection of splicing forgery in digital images. Multimed Tools Appl 79(43):32037\u201332063","journal-title":"Multimed Tools Appl"},{"issue":"2","key":"14016_CR16","doi-asserted-by":"publisher","first-page":"561","DOI":"10.3906\/elk-2001-138","volume":"29","author":"N Kaur","year":"2021","unstructured":"Kaur N, Jindal N, Singh K (2021) Efficient hybrid passive method for the detection and localization of copy-move and spliced images. Turk J Electr Eng Co 29(2):561\u2013582","journal-title":"Turk J Electr Eng Co"},{"issue":"14","key":"14016_CR17","doi-asserted-by":"publisher","first-page":"18269","DOI":"10.1007\/s11042-017-5374-6","volume":"77","author":"Y Liu","year":"2018","unstructured":"Liu Y, Guan Q, Zhao X (2018) Copy-move forgery detection based on convolutional kernel network. Multimed Tools Appl 77(14):18269\u201318293","journal-title":"Multimed Tools Appl"},{"key":"14016_CR18","doi-asserted-by":"crossref","unstructured":"Liu L, Zhao Y, Ni R, Tian Q (2018) Copy-move forgery localization using convolutional neural networks and CFA features. Int J Digit Crime Forensic 10(4):140\u2013155","DOI":"10.4018\/IJDCF.2018100110"},{"key":"14016_CR19","doi-asserted-by":"publisher","first-page":"8197","DOI":"10.1007\/s11042-019-08343-0","volume":"79","author":"KB Meena","year":"2020","unstructured":"Meena KB, Tyagi V (2020) A hybrid copy-move image forgery detection technique based on Fourier-Mellin and scale invariant feature transforms. Multimed Tools Appl 79:8197\u20138212","journal-title":"Multimed Tools Appl"},{"key":"14016_CR20","doi-asserted-by":"publisher","first-page":"3391","DOI":"10.1109\/TCSVT.2020.3043026","volume":"31","author":"X Ning","year":"2020","unstructured":"Ning X, Gong K, Li W, Zhang L, Bai X, Tian S (2020) Feature refinement and filter network for person re-identification. IEEE Trans Circuits Syst Video Technol 31:3391\u20133402","journal-title":"IEEE Trans Circuits Syst Video Technol"},{"key":"14016_CR21","doi-asserted-by":"publisher","first-page":"801","DOI":"10.1016\/j.neucom.2020.05.106","volume":"453","author":"X Ning","year":"2021","unstructured":"Ning X, Gong K, Li W, Zhang L (2021) JWSAA: joint weak saliency and attention aware for person re-identification. Neurocomputing 453:801\u2013811","journal-title":"Neurocomputing"},{"key":"14016_CR22","doi-asserted-by":"crossref","unstructured":"Pal KK, Sudeep KS (2016) Preprocessing for image classification by convolutional neural networks. In IEEE International Conference on Recent Trends in Electronics, Information & Communication Technology (RTEICT).\u00a0IEEE, pp 1778\u20131781","DOI":"10.1109\/RTEICT.2016.7808140"},{"issue":"16","key":"14016_CR23","doi-asserted-by":"publisher","first-page":"23535","DOI":"10.1007\/s11042-019-7629-x","volume":"78","author":"CS Prakash","year":"2019","unstructured":"Prakash CS, Panzade PP, Om H, Maheshkar S (2019) Detection of copy-move forgery using AKAZE and SIFT keypoint extraction. Multimed Tools Appl 78(16):23535\u201323558","journal-title":"Multimed Tools Appl"},{"issue":"8","key":"14016_CR24","doi-asserted-by":"publisher","first-page":"1705","DOI":"10.1109\/TIFS.2015.2423261","volume":"10","author":"CM Pun","year":"2015","unstructured":"Pun CM, Yuan XC, Bi XL (2015) Image forgery detection using adaptive oversegmentation and feature point matching. IEEE Trans Inf Forensics Secur 10(8):1705\u20131716","journal-title":"IEEE Trans Inf Forensics Secur"},{"key":"14016_CR25","doi-asserted-by":"crossref","unstructured":"Rao Y, Ni J (2016) A deep learning approach to detection of splicing and copy-move forgeries in images. In: IEEE international workshop on information forensics and security.\u00a0IEEE, pp 1\u20136","DOI":"10.1109\/WIFS.2016.7823911"},{"issue":"3","key":"14016_CR26","doi-asserted-by":"publisher","first-page":"59","DOI":"10.3390\/jimaging7030059","volume":"7","author":"Y Rodriguez-Ortega","year":"2021","unstructured":"Rodriguez-Ortega Y, Ballesteros DM, Renza D (2021) Copy-move forgery detection (CMFD) using deep learning for image and video forensics. J Imaging 7(3):59","journal-title":"J Imaging"},{"key":"14016_CR27","unstructured":"Ruder S (2016) An overview of gradient descent optimization algorithms. ArXiv arXiv:1609.04747"},{"key":"14016_CR28","doi-asserted-by":"crossref","unstructured":"Tahaoglu G, Ulutas G, Ustubioglu B, Nabiyev VV (2021) Improved copy move forgery detection method via L* a* b* color space and enhanced localization technique. Multimed Tools Appl 80:23419\u201323456","DOI":"10.1007\/s11042-020-10241-9"},{"key":"14016_CR29","doi-asserted-by":"crossref","unstructured":"Tinnathi S, Sudhavani G (2021) An efficient copy move forgery detection using adaptive watershed segmentation with AGSO and hybrid feature extraction. J Vis Commun Image Represent 74:102966","DOI":"10.1016\/j.jvcir.2020.102966"},{"issue":"12","key":"14016_CR30","doi-asserted-by":"publisher","first-page":"706","DOI":"10.3390\/sym10120706","volume":"10","author":"C Wang","year":"2018","unstructured":"Wang C, Zhang Z, Zhou X (2018) An image copy-move forgery detection scheme based on A-KAZE and SURF features. Symmetry 10(12):706\u2013726","journal-title":"Symmetry"},{"key":"14016_CR31","unstructured":"Wang X, Zheng Z, He Y, Yan F, Zeng Z, Yang Y (2020) Progressive local filter pruning for image retrieval acceleration. ArXiv arXiv:2001.08878"},{"key":"14016_CR32","doi-asserted-by":"crossref","unstructured":"Yang F, Li J, Lu W, Weng J (2017) Copy-move forgery detection based on hybrid features. Eng Appl Artif Intell 59:73\u201383","DOI":"10.1016\/j.engappai.2016.12.022"},{"key":"14016_CR33","doi-asserted-by":"crossref","unstructured":"Zhang Z, Wang C, Zhou X (2018) A survey on passive image copy-move forgery detection. J Inf Process Syst 14(1):6\u201331","DOI":"10.1155\/2018\/6853696"},{"key":"14016_CR34","doi-asserted-by":"crossref","unstructured":"Zhong JL, Pun CM (2019) An end-to-end dense-inceptionNet for image copy-move forgery detection. IEEE Trans Info Forensics Secur 15:2134\u20132146","DOI":"10.1109\/TIFS.2019.2957693"}],"container-title":["Multimedia Tools and Applications"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s11042-022-14016-2.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s11042-022-14016-2\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s11042-022-14016-2.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2023,4,20]],"date-time":"2023-04-20T14:56:15Z","timestamp":1682002575000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s11042-022-14016-2"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022,10,12]]},"references-count":34,"journal-issue":{"issue":"12","published-print":{"date-parts":[[2023,5]]}},"alternative-id":["14016"],"URL":"https:\/\/doi.org\/10.1007\/s11042-022-14016-2","relation":{},"ISSN":["1380-7501","1573-7721"],"issn-type":[{"value":"1380-7501","type":"print"},{"value":"1573-7721","type":"electronic"}],"subject":[],"published":{"date-parts":[[2022,10,12]]},"assertion":[{"value":"25 August 2021","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"12 January 2022","order":2,"name":"revised","label":"Revised","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"23 September 2022","order":3,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"12 October 2022","order":4,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}}]}}