Keypoint based comprehensive copy‐move forgery detection
Verifying the authenticity of a digital image has been challenging problem. The simplest of the image tampering tricks is the copy‐move forgery. In copy‐move forgery copied portion of the image is pasted on another part of the same image. Geometrical transformations are used on the copied portions o...
Saved in:
| Published in: | IET image processing Vol. 15; no. 6; pp. 1298 - 1309 |
|---|---|
| Main Authors: | , , , |
| Format: | Journal Article |
| Language: | English |
| Published: |
Wiley
01.05.2021
|
| Subjects: | |
| ISSN: | 1751-9659, 1751-9667 |
| Online Access: | Get full text |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| Abstract | Verifying the authenticity of a digital image has been challenging problem. The simplest of the image tampering tricks is the copy‐move forgery. In copy‐move forgery copied portion of the image is pasted on another part of the same image. Geometrical transformations are used on the copied portions of the image before pasting it for the tampered image to look realistic and visually convincing. To make it more complex, other processing approaches may also be applied in the forged region for hiding traces of forgery. These processings are the scale, rotation, JPEG compression, and AWGN. In this paper, an approach based on features of the CenSurE keypoint detector and FREAK descriptor is proposed. This combination has novelty in itself as it has never been used for this purpose before to the best of authors' literature studies. CenSurE detectors are fast and give stable and accurate output even in the case of rotated images, which we club with binary descriptor FREAK. Hierarchical clustering and Neighbourhood search is applied in such a way that it can locate and detect multiple copy‐move forgeries. The authors are hopeful that the proposed approach may be used in real‐time image authentication and copy‐move forgery detection. |
|---|---|
| AbstractList | Verifying the authenticity of a digital image has been challenging problem. The simplest of the image tampering tricks is the copy‐move forgery. In copy‐move forgery copied portion of the image is pasted on another part of the same image. Geometrical transformations are used on the copied portions of the image before pasting it for the tampered image to look realistic and visually convincing. To make it more complex, other processing approaches may also be applied in the forged region for hiding traces of forgery. These processings are the scale, rotation, JPEG compression, and AWGN. In this paper, an approach based on features of the CenSurE keypoint detector and FREAK descriptor is proposed. This combination has novelty in itself as it has never been used for this purpose before to the best of authors' literature studies. CenSurE detectors are fast and give stable and accurate output even in the case of rotated images, which we club with binary descriptor FREAK. Hierarchical clustering and Neighbourhood search is applied in such a way that it can locate and detect multiple copy‐move forgeries. The authors are hopeful that the proposed approach may be used in real‐time image authentication and copy‐move forgery detection. Abstract Verifying the authenticity of a digital image has been challenging problem. The simplest of the image tampering tricks is the copy‐move forgery. In copy‐move forgery copied portion of the image is pasted on another part of the same image. Geometrical transformations are used on the copied portions of the image before pasting it for the tampered image to look realistic and visually convincing. To make it more complex, other processing approaches may also be applied in the forged region for hiding traces of forgery. These processings are the scale, rotation, JPEG compression, and AWGN. In this paper, an approach based on features of the CenSurE keypoint detector and FREAK descriptor is proposed. This combination has novelty in itself as it has never been used for this purpose before to the best of authors' literature studies. CenSurE detectors are fast and give stable and accurate output even in the case of rotated images, which we club with binary descriptor FREAK. Hierarchical clustering and Neighbourhood search is applied in such a way that it can locate and detect multiple copy‐move forgeries. The authors are hopeful that the proposed approach may be used in real‐time image authentication and copy‐move forgery detection. |
| Author | Roy, Anil K. Mitra, Suman K. Sharma, Rajat Diwan, Anjali |
| Author_xml | – sequence: 1 givenname: Anjali surname: Diwan fullname: Diwan, Anjali email: anjali.diwan@ieee.org organization: DA‐IICT – sequence: 2 givenname: Rajat surname: Sharma fullname: Sharma, Rajat organization: DA‐IICT – sequence: 3 givenname: Anil K. surname: Roy fullname: Roy, Anil K. organization: DA‐IICT – sequence: 4 givenname: Suman K. surname: Mitra fullname: Mitra, Suman K. organization: DA‐IICT |
| BookMark | eNp9kM1Kw0AQxxepYFu9-AQ9C6m7m2yS9SbFj2JBET0vk82sbkmzYROU3HwEn9EncdtIDyLCwHww_x8z_wkZ1a5GQk4ZnTOayHPbeD5nnFFxQMYsEyySaZqN9rWQR2TStmtKhaS5GJOLO-wbZ-tuVkCL5Uy7TePxFevWvmHomv7r43PjQm2cf0Hfz0rsUHfW1cfk0EDV4slPnpLn66unxW20ur9ZLi5XkY4zISLNRZ7yrEyBZbGkmlPMdCEpQxNOgCSELAqeS4gzY2JMYs5i0MYkIkNI83hKlgO3dLBWjbcb8L1yYNVuEM5S4DurK1SAhSzBYJkymcQlhRQDKteIRhcgeGCdDSztXdt6NHseo2rroNo6qHYOhmX6a1nbDravdx5s9beEDZJ3W2H_D1wtHx75oPkG-i6HXg |
| CitedBy_id | crossref_primary_10_1109_ACCESS_2024_3397466 crossref_primary_10_1007_s11042_024_18399_2 crossref_primary_10_1007_s11042_023_17485_1 crossref_primary_10_1080_13682199_2024_2428448 crossref_primary_10_1007_s10791_025_09658_3 crossref_primary_10_1007_s42979_023_02388_7 crossref_primary_10_1080_23311916_2024_2424466 crossref_primary_10_32604_cmc_2025_055739 crossref_primary_10_1109_ACCESS_2022_3172273 crossref_primary_10_1109_ACCESS_2024_3380460 crossref_primary_10_1109_ACCESS_2023_3304728 crossref_primary_10_1007_s11042_023_17475_3 crossref_primary_10_1016_j_patcog_2023_109778 crossref_primary_10_1038_s41598_022_19325_y crossref_primary_10_3390_s24134143 |
| Cites_doi | 10.1049/iet-ipr.2018.5356 10.1109/ICIP.2016.7532339 10.1109/TIFS.2011.2129512 10.1007/s11042-019-7277-1 10.1109/ACCESS.2019.2907316 10.1016/j.image.2017.05.010 10.1007/11744023_32 10.1109/ICCV.2011.6126542 10.1023/B:VISI.0000029664.99615.94 10.1109/IDAP.2017.8090251 10.1049/iet-ipr.2019.0842 10.1016/j.forsciint.2018.05.047 10.1007/s11042-019-7342-9 10.1007/978-3-540-88693-8_8 10.1109/ICCV.2011.6126544 10.1016/j.ins.2017.08.044 10.1109/ACCESS.2018.2871952 10.1016/j.ins.2019.09.085 10.1109/ACCESS.2020.2964516 10.1109/ACCESS.2020.2974804 10.1109/CVPR.2012.6247715 10.1109/TIFS.2012.2218597 10.1109/ICIIP47207.2019.8985823 10.1007/s11042-019-7713-2 10.1109/ACCESS.2019.2955308 10.1109/WVC.2019.8876915 10.1049/iet-ipr.2017.0441 10.1007/s11042-019-07930-5 10.1007/s11042-018-6595-z 10.1109/ICIP.2014.7026075 10.1016/j.jvcir.2017.04.004 10.1016/j.jisa.2020.102510 10.1016/j.patcog.2018.03.028 |
| ContentType | Journal Article |
| Copyright | 2020 The Authors. published by John Wiley & Sons Ltd on behalf of The Institution of Engineering and Technology |
| Copyright_xml | – notice: 2020 The Authors. published by John Wiley & Sons Ltd on behalf of The Institution of Engineering and Technology |
| DBID | 24P AAYXX CITATION DOA |
| DOI | 10.1049/ipr2.12105 |
| DatabaseName | Wiley Online Library Open Access CrossRef DOAJ Directory of Open Access Journals |
| DatabaseTitle | CrossRef |
| DatabaseTitleList | CrossRef |
| Database_xml | – sequence: 1 dbid: 24P name: Wiley Online Library Open Access url: https://authorservices.wiley.com/open-science/open-access/browse-journals.html sourceTypes: Publisher – sequence: 2 dbid: DOA name: Openly Available Collection - DOAJ url: https://www.doaj.org/ sourceTypes: Open Website |
| DeliveryMethod | fulltext_linktorsrc |
| Discipline | Applied Sciences |
| EISSN | 1751-9667 |
| EndPage | 1309 |
| ExternalDocumentID | oai_doaj_org_article_aeb9dafed61943d0a6e3ac8ceefcba52 10_1049_ipr2_12105 IPR212105 |
| Genre | article |
| GroupedDBID | .DC 0R~ 1OC 24P 29I 4.4 5GY 6IK 8FE 8FG 8VB AAHHS AAHJG AAJGR ABJCF ABQXS ACCFJ ACCMX ACESK ACGFS ACIWK ACXQS ADZOD AEEZP AENEX AEQDE AFKRA AIWBW AJBDE ALMA_UNASSIGNED_HOLDINGS ALUQN ARAPS AVUZU BENPR BGLVJ CCPQU CS3 DU5 EBS EJD ESX GROUPED_DOAJ HCIFZ HZ~ IAO IFIPE IPLJI ITC JAVBF K1G L6V LAI M43 M7S MCNEO MS~ O9- OCL OK1 P2P P62 PTHSS QWB RIE RNS ROL RUI S0W ZL0 AAMMB AAYXX AEFGJ AFFHD AGXDD AIDQK AIDYY CITATION IDLOA PHGZM PHGZT PQGLB WIN |
| ID | FETCH-LOGICAL-c3755-c258627d6a17390c20e7cb901ef908a48a49bb289a37ff3e43213acff457ea683 |
| IEDL.DBID | DOA |
| ISICitedReferencesCount | 18 |
| ISICitedReferencesURI | http://www.webofscience.com/api/gateway?GWVersion=2&SrcApp=Summon&SrcAuth=ProQuest&DestLinkType=CitingArticles&DestApp=WOS_CPL&KeyUT=000603453100001&url=https%3A%2F%2Fcvtisr.summon.serialssolutions.com%2F%23%21%2Fsearch%3Fho%3Df%26include.ft.matches%3Dt%26l%3Dnull%26q%3D |
| ISSN | 1751-9659 |
| IngestDate | Fri Oct 03 12:45:45 EDT 2025 Wed Oct 29 21:17:17 EDT 2025 Tue Nov 18 22:38:59 EST 2025 Wed Jan 22 16:31:06 EST 2025 |
| IsDoiOpenAccess | true |
| IsOpenAccess | true |
| IsPeerReviewed | true |
| IsScholarly | true |
| Issue | 6 |
| Language | English |
| License | Attribution |
| LinkModel | DirectLink |
| MergedId | FETCHMERGED-LOGICAL-c3755-c258627d6a17390c20e7cb901ef908a48a49bb289a37ff3e43213acff457ea683 |
| OpenAccessLink | https://doaj.org/article/aeb9dafed61943d0a6e3ac8ceefcba52 |
| PageCount | 12 |
| ParticipantIDs | doaj_primary_oai_doaj_org_article_aeb9dafed61943d0a6e3ac8ceefcba52 crossref_primary_10_1049_ipr2_12105 crossref_citationtrail_10_1049_ipr2_12105 wiley_primary_10_1049_ipr2_12105_IPR212105 |
| PublicationCentury | 2000 |
| PublicationDate | May 2021 2021-05-00 2021-05-01 |
| PublicationDateYYYYMMDD | 2021-05-01 |
| PublicationDate_xml | – month: 05 year: 2021 text: May 2021 |
| PublicationDecade | 2020 |
| PublicationTitle | IET image processing |
| PublicationYear | 2021 |
| Publisher | Wiley |
| Publisher_xml | – name: Wiley |
| References | 2019; 7 2017; 418 2004; 60 2012 2011 2018; 289 2019; 78 2017; 46 2018; 81 2008 2020; 14 2006 2020; 13 2020; 54 2011; 6 2020; 8 2018; 6 2020; 7 2018; 2018 2020; 52 2017; 57 2017; 12 2020; 512 2019 2017 2016 2014 2013 2012; 7 e_1_2_7_6_1 e_1_2_7_5_1 e_1_2_7_4_1 e_1_2_7_3_1 e_1_2_7_9_1 e_1_2_7_8_1 e_1_2_7_7_1 e_1_2_7_19_1 e_1_2_7_18_1 e_1_2_7_17_1 e_1_2_7_16_1 e_1_2_7_2_1 e_1_2_7_15_1 e_1_2_7_14_1 e_1_2_7_13_1 e_1_2_7_12_1 e_1_2_7_11_1 e_1_2_7_10_1 e_1_2_7_26_1 e_1_2_7_27_1 e_1_2_7_28_1 e_1_2_7_29_1 e_1_2_7_30_1 Wang H. (e_1_2_7_21_1) 2018; 2018 e_1_2_7_31_1 e_1_2_7_24_1 e_1_2_7_32_1 e_1_2_7_23_1 e_1_2_7_22_1 e_1_2_7_34_1 e_1_2_7_35_1 e_1_2_7_20_1 e_1_2_7_36_1 e_1_2_7_37_1 e_1_2_7_38_1 Meena K.B. (e_1_2_7_25_1) 2020; 52 Tralic D. (e_1_2_7_33_1) 2013 |
| References_xml | – volume: 78 start-page: 25591 year: 2019 end-page: 25609 article-title: A probabilistic framework for copy‐move forgery detection based on Markov random field publication-title: Multim. Tools Appl. – start-page: 397 year: 2019 end-page: 402 – volume: 8 start-page: 36 863 year: 2020 end-page: 36 875 article-title: Copy‐move forgery detection based on keypoint clustering and similar neighborhood search algorithm publication-title: IEEE Access – volume: 8 start-page: 11 815 year: 2020 end-page: 11 823 article-title: Passive image forgery detection based on the demosaicing algorithm and jpeg compression publication-title: IEEE Access – volume: 78 start-page: 20739 year: 2019 end-page: 20763 article-title: Region duplication detection based on hybrid feature and evaluative clustering publication-title: Multim. Tools Appl. – start-page: 96 year: 2019 end-page: 102 – volume: 2018 year: 2018 article-title: Perceptual hashing‐based image copy‐move forgery detection publication-title: Security Commun. Netw. – volume: 7 start-page: 170 032 year: 2020 end-page: 170 047 article-title: An image copy‐move forgery detection method based on SURF and PCET publication-title: IEEE Access – start-page: 1 year: 2017 end-page: 7 – volume: 6 start-page: 1099 issue: 3 year: 2011 end-page: 1110 article-title: A sift‐based forensic method for copy–move attack detection and transformation recovery publication-title: IEEE Trans. Inf. Forensics Secur. – volume: 54 year: 2020 article-title: A robust copy‐move forgery detection technique based on discrete cosine transform and cellular automata publication-title: J. Inf. Security Appl. – volume: 418 start-page: 531 year: 2017 end-page: 545 article-title: Fast reflective offset‐guided searching method for copy‐move forgery detection publication-title: Inf. Sci. – volume: 289 start-page: 268 year: 2018 end-page: 269 article-title: Digital forensics in a post‐truth age publication-title: Forensic Sci. Int. – start-page: 404 year: 2006 end-page: 417 – volume: 60 start-page: 91 issue: 2 year: 2004 end-page: 110 article-title: Distinctive image features from scale‐invariant keypoints publication-title: Int. J. Comput. Vision – start-page: 2564 year: 2011 end-page: 2571 – volume: 512 start-page: 675 year: 2020 end-page: 692 article-title: Two‐pass hashing feature representation and searching method for copy‐move forgery detection publication-title: Inf. Sci. – volume: 6 start-page: 56 637 year: 2018 end-page: 56 646 article-title: Fractional quaternion Zernike moments for robust color image copy‐move forgery detection publication-title: IEEE Access – start-page: 510 year: 2012 end-page: 517 – volume: 57 start-page: 113 year: 2017 end-page: 125 article-title: An improved method for sift‐based copy–move forgery detection using non‐maximum value suppression and optimized j‐linkage publication-title: Signal Process. Image Commun. – start-page: 161 year: 2016 end-page: 165 – start-page: 2548 year: 2011 end-page: 2555 – volume: 52 year: 2020 article-title: A copy‐move image forgery detection technique based on Tetrolet transform publication-title: J. Inf. Security Appl. – start-page: 5312 year: 2014 end-page: 5316 – volume: 81 start-page: 161 year: 2018 end-page: 175 article-title: Fast copy‐move forgery detection using local bidirectional coherency error refinement publication-title: Pattern Recogn. – start-page: 102 year: 2008 end-page: 115 – volume: 78 start-page: 8057 issue: 7 year: 2019 end-page: 8073 article-title: Fractional quaternion cosine transform and its application in color image copy‐move forgery detection publication-title: Multim. Tools Appl. – volume: 7 start-page: 40 550 year: 2019 end-page: 40 568 article-title: Copy‐move forgery detection: A state‐of‐the‐art technical review and analysis publication-title: IEEE Access – volume: 78 start-page: 31 387 issue: 22 year: 2019 end-page: 31 413 article-title: Copy move forgery detection based on keypoint and patch match publication-title: Multim. Tools Appl. – volume: 12 start-page: 167 issue: 2 year: 2017 end-page: 178 article-title: CMFD: A detailed review of block based and key feature based techniques in image copy‐move forgery detection publication-title: IET Image Proc. – volume: 14 start-page: 462 issue: 3 year: 2020 end-page: 471 article-title: Enhanced copy past forgery detection in digital images using scale‐invariant feature transform publication-title: IET Image Proc. – volume: 13 start-page: 1437 issue: 9 year: 2020 end-page: 1446 article-title: Copy‐for‐duplication forgery detection in colour images using QPCETMs and sub‐image approach publication-title: IET Image Proc. – volume: 46 start-page: 219 year: 2017 end-page: 232 article-title: Sift‐symmetry: A robust detection method for copy‐move forgery with reflection attack publication-title: J. Visual Commun. Image Rep. – start-page: 49 year: 2013 end-page: 54 – volume: 7 start-page: 1841 issue: 6 year: 2012 end-page: 1854 article-title: An evaluation of popular copy‐move forgery detection approaches publication-title: IEEE Trans. Inf. Forensics Secur. – volume: 78 start-page: 20 655 issue: 15 year: 2019 end-page: 20 678 article-title: Copy‐move forgery detection based on multifractals publication-title: Multim. Tools Appl. – ident: e_1_2_7_11_1 doi: 10.1049/iet-ipr.2018.5356 – ident: e_1_2_7_34_1 doi: 10.1109/ICIP.2016.7532339 – ident: e_1_2_7_32_1 doi: 10.1109/TIFS.2011.2129512 – ident: e_1_2_7_9_1 doi: 10.1007/s11042-019-7277-1 – ident: e_1_2_7_4_1 doi: 10.1109/ACCESS.2019.2907316 – ident: e_1_2_7_16_1 doi: 10.1016/j.image.2017.05.010 – volume: 52 start-page: 102481 year: 2020 ident: e_1_2_7_25_1 article-title: A copy‐move image forgery detection technique based on Tetrolet transform publication-title: J. Inf. Security Appl. – ident: e_1_2_7_27_1 doi: 10.1007/11744023_32 – ident: e_1_2_7_29_1 doi: 10.1109/ICCV.2011.6126542 – ident: e_1_2_7_26_1 doi: 10.1023/B:VISI.0000029664.99615.94 – ident: e_1_2_7_15_1 doi: 10.1109/IDAP.2017.8090251 – ident: e_1_2_7_23_1 doi: 10.1049/iet-ipr.2019.0842 – ident: e_1_2_7_3_1 doi: 10.1016/j.forsciint.2018.05.047 – ident: e_1_2_7_36_1 doi: 10.1007/s11042-019-7342-9 – ident: e_1_2_7_7_1 doi: 10.1007/978-3-540-88693-8_8 – ident: e_1_2_7_28_1 doi: 10.1109/ICCV.2011.6126544 – ident: e_1_2_7_35_1 doi: 10.1016/j.ins.2017.08.044 – ident: e_1_2_7_17_1 doi: 10.1109/ACCESS.2018.2871952 – start-page: 49 volume-title: Proceedings ELMAR‐2013 year: 2013 ident: e_1_2_7_33_1 – ident: e_1_2_7_2_1 – ident: e_1_2_7_12_1 doi: 10.1016/j.ins.2019.09.085 – ident: e_1_2_7_24_1 doi: 10.1109/ACCESS.2020.2964516 – ident: e_1_2_7_38_1 doi: 10.1109/ACCESS.2020.2974804 – ident: e_1_2_7_8_1 doi: 10.1109/CVPR.2012.6247715 – ident: e_1_2_7_30_1 doi: 10.1109/TIFS.2012.2218597 – ident: e_1_2_7_10_1 doi: 10.1109/ICIIP47207.2019.8985823 – ident: e_1_2_7_20_1 doi: 10.1007/s11042-019-7713-2 – volume: 2018 start-page: 6853696 year: 2018 ident: e_1_2_7_21_1 article-title: Perceptual hashing‐based image copy‐move forgery detection publication-title: Security Commun. Netw. – ident: e_1_2_7_22_1 doi: 10.1109/ACCESS.2019.2955308 – ident: e_1_2_7_6_1 doi: 10.1109/WVC.2019.8876915 – ident: e_1_2_7_5_1 doi: 10.1049/iet-ipr.2017.0441 – ident: e_1_2_7_18_1 doi: 10.1007/s11042-019-07930-5 – ident: e_1_2_7_19_1 doi: 10.1007/s11042-018-6595-z – ident: e_1_2_7_31_1 doi: 10.1109/ICIP.2014.7026075 – ident: e_1_2_7_14_1 doi: 10.1016/j.jvcir.2017.04.004 – ident: e_1_2_7_13_1 doi: 10.1016/j.jisa.2020.102510 – ident: e_1_2_7_37_1 doi: 10.1016/j.patcog.2018.03.028 |
| SSID | ssj0059085 |
| Score | 2.338709 |
| Snippet | Verifying the authenticity of a digital image has been challenging problem. The simplest of the image tampering tricks is the copy‐move forgery. In copy‐move... Abstract Verifying the authenticity of a digital image has been challenging problem. The simplest of the image tampering tricks is the copy‐move forgery. In... |
| SourceID | doaj crossref wiley |
| SourceType | Open Website Enrichment Source Index Database Publisher |
| StartPage | 1298 |
| SubjectTerms | Computer vision and image processing techniques Image and video coding Image recognition Optical, image and video signal processing |
| SummonAdditionalLinks | – databaseName: Wiley Online Library Open Access dbid: 24P link: http://cvtisr.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwpV1LS8QwEA6LevDi-sT1RUEvCsU2j6YRLyouirAsorC3kuaBC9qWbhX25k_wN_pLTNJ2ZUEEEXpIw5Q2k0xmkk6-D4CjmGgmEaS-olD6WIexzzHVvqmMqMZRJHTsyCboYBCPRmzYAeftWZgaH2K24WYtw83X1sB5WrOQmKDWdOK4KKHFRrAApothiGJL3ADxsJ2HLZk3ccchLZF8RFgLTorZ6fezc-7IofbPR6nOzfS7__vAVbDShJfeRT0e1kBHZeug24SaXmPIkw1wdqemRT7OKs-6MenZzPJSPdXZ7OaumH6-f7zkpqxzd27ak6pyWVvZJnjsXz9c3fgNjYIvECXEF5CYZQuVEQ8pYoGAgaIiNXGA0kZFHJuLpalZeHFEtUYKIxgiLrTGhCoexWgLLGR5praBF1BplpCIcgUlxoimXBGCCIeCEM512gPHrTYT0WCMW6qL58T968YssUpJnFJ64HAmW9TIGj9KXdpOmUlYNGxXYRqfNMaVcJUyybWSdksGyYBHyjQgNv5fi5QT2AMnrqN-eU9yO7yHrrTzF-FdsAxtkovLgNwDC1X5qvbBknirxpPywI3HL47p454 priority: 102 providerName: Wiley-Blackwell |
| Title | Keypoint based comprehensive copy‐move forgery detection |
| URI | https://onlinelibrary.wiley.com/doi/abs/10.1049%2Fipr2.12105 https://doaj.org/article/aeb9dafed61943d0a6e3ac8ceefcba52 |
| Volume | 15 |
| WOSCitedRecordID | wos000603453100001&url=https%3A%2F%2Fcvtisr.summon.serialssolutions.com%2F%23%21%2Fsearch%3Fho%3Df%26include.ft.matches%3Dt%26l%3Dnull%26q%3D |
| hasFullText | 1 |
| inHoldings | 1 |
| isFullTextHit | |
| isPrint | |
| journalDatabaseRights | – providerCode: PRVAON databaseName: Openly Available Collection - DOAJ customDbUrl: eissn: 1751-9667 dateEnd: 20241231 omitProxy: false ssIdentifier: ssj0059085 issn: 1751-9659 databaseCode: DOA dateStart: 20210101 isFulltext: true titleUrlDefault: https://www.doaj.org/ providerName: Directory of Open Access Journals – providerCode: PRVWIB databaseName: Wiley Online Library Free Content customDbUrl: eissn: 1751-9667 dateEnd: 99991231 omitProxy: false ssIdentifier: ssj0059085 issn: 1751-9659 databaseCode: WIN dateStart: 20130101 isFulltext: true titleUrlDefault: https://onlinelibrary.wiley.com providerName: Wiley-Blackwell – providerCode: PRVWIB databaseName: Wiley Online Library Open Access customDbUrl: eissn: 1751-9667 dateEnd: 99991231 omitProxy: false ssIdentifier: ssj0059085 issn: 1751-9659 databaseCode: 24P dateStart: 20130101 isFulltext: true titleUrlDefault: https://authorservices.wiley.com/open-science/open-access/browse-journals.html providerName: Wiley-Blackwell |
| link | http://cvtisr.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwrV1LS8NAEB60ePDiW6yPEtCLQmi7j2ziTcViEUoRxd7CZh9Y0CSkUejNn-Bv9Je4u0lLBdGLEMJmGdjdmWRnhsx-H8BJSHUkMWK-Ykj6RHdDnxOmfdMZME2CQOjQkU2wwSAcjaLhAtWXrQmr4IErxbW5SiLJtZI23caywwOFuQjN3q5FwqnbfU3UM0umqj3YEnlTdxTSksgHNJoBk5KoPc4LZDEVLGHdgityiP3fI1TnYnobsFbHht5FNadNWFLpFqzXcaJXf4WTbTi_VdM8G6elZ32Q9GxZeKGeqlJ085RPP98_XjLT1pk79OxJVbqSq3QHHnrX91c3fs2B4AvMKPUFoibnYDLgXYajjkAdxURinLjSZo2cmCtKEpM1ccy0xopg1DX60ZpQpngQ4l1opFmq9sDrMGnyP8y4QpIQzBKuKMWUI0Ep5zppwulMHbGoAcItT8Vz7H5Ukyi2qoud6ppwPJfNK1iMH6UurVbnEhbK2nWYxce1geO_DNyEM2eTX8aJ-8M75Fr7_zHiAawiW7niyhoPoVEWr-oIVsRbOZ4ULVhGZNhyr5u5P_YHX3y_3Fo |
| linkProvider | Directory of Open Access Journals |
| linkToHtml | http://cvtisr.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwpV1LS8NAEF5EBb1Yn1ifAb0oBNt9ZBNvKpaW1lKkYm9hsw8saFLaKvTmT_A3-kvc2aSVgggi5LBZJiQ7u7M7M5n5BqHTkJlIEcx9zbHyqamGvqDc-LYz4IYGgTShKzbB2-2w14s6RWwO5MLk-BAzhxtIhtuvQcDBIZ0bnBRAMvuDIQZwBEAwXaJW04DKDY-N9nQjhmrezOVDQiX5gEVTdFIaXXw_O3ceOdj-eTXVnTO10j-_cB2tFQqmd5WviA20oNNNVCqUTa8Q5dEWumzqySDrp2MPDjLlQWz5UD_l8ez2bjD5fP94yWzbZC5z2lN67OK20m30ULvt3tT9opCCLwlnzJeYWcOFq0BUOYkqElc0l4nVBLSxPBLUXlGSWNNLEG4M0ZTgKhHSGMq4FkFIdtBimqV6F3kVrqwRSbjQWFFKeCI0Y4QJLBkTwiRldDZlZywLlHEodvEcu7_dNIqBKbFjShmdzGgHObbGj1TXMCszCsDDdh128HEhXrHQSaSE0QqcMkRVRKDtAEKrARiZCIbL6NzN1C_viRude-xae38hPkYr9e5dK2412s19tIoh5MXFQx6gxfHwVR-iZfk27o-GR25xfgG0uuf2 |
| linkToPdf | http://cvtisr.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwpV3dS8MwEA-iIr74Lc7Pgr4oFLd8NK1vfg3HZAxR8K2kyQUH2pVtCr75J_g3-peYS7uJIIIIfUjDlTaXu-QuvfsdIQexsIlhVIYgqQm5bcSh4tKGrjOSlkeRtrEvNiE7nfj-PulWsTmYC1PiQ0wO3FAz_HqNCg6FsaXDyREks1cMKIIjIILpDBeygUJNeXe8EGM1b-HzIbGSfCSSMTopT46_nv22H3nY_u9mqt9nmov__MIlslAZmMFpKRHLZAryFbJYGZtBpcrDVXLShtei38tHAW5kJsDY8gE8lPHs7q54_Xh7f-q7tu37zOnAwMjHbeVr5K55eXt-FVaFFELNpBChpsI5LtJEqiFZUte0DlJnzhIA63ikuLuSLHOul2LSWgac0QZT2lrHVVBRzNbJdN7PYYMEdWmcE8mkAmo4ZzJTIAQTimohlLJZjRyO2ZnqCmUci108pv5vN09SZErqmVIj-xPaosTW-JHqDGdlQoF42L7DDT6t1CtVkCVGWTB4KMNMXUXgBhA7C8DqTAlaI0d-pn55T9rq3lDf2vwL8R6Z61400-tWp71F5ilGvPhwyG0yPRo8ww6Z1S-j3nCw62XzE--q5w0 |
| openUrl | ctx_ver=Z39.88-2004&ctx_enc=info%3Aofi%2Fenc%3AUTF-8&rfr_id=info%3Asid%2Fsummon.serialssolutions.com&rft_val_fmt=info%3Aofi%2Ffmt%3Akev%3Amtx%3Ajournal&rft.genre=article&rft.atitle=Keypoint+based+comprehensive+copy%E2%80%90move+forgery+detection&rft.jtitle=IET+image+processing&rft.au=Diwan%2C+Anjali&rft.au=Sharma%2C+Rajat&rft.au=Roy%2C+Anil+K.&rft.au=Mitra%2C+Suman+K.&rft.date=2021-05-01&rft.issn=1751-9659&rft.eissn=1751-9667&rft.volume=15&rft.issue=6&rft.spage=1298&rft.epage=1309&rft_id=info:doi/10.1049%2Fipr2.12105&rft.externalDBID=n%2Fa&rft.externalDocID=10_1049_ipr2_12105 |
| thumbnail_l | http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/lc.gif&issn=1751-9659&client=summon |
| thumbnail_m | http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/mc.gif&issn=1751-9659&client=summon |
| thumbnail_s | http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/sc.gif&issn=1751-9659&client=summon |