Distinguishable zero-watermarking scheme with similarity-based retrieval for digital rights Management of Fundus Image

Zero-watermarking scheme can provide durable and distortion-free digital rights management (DRM) for fundus image which plays an important role in diagnosis of ocular diseases. However, existing zero-watermarking schemes probably identify a similar fundus image as a copy, because they rarely conside...

Ausführliche Beschreibung

Gespeichert in:
Bibliographische Detailangaben
Veröffentlicht in:Multimedia tools and applications 2018-11, Vol.77 (21), p.28685-28708
Hauptverfasser: Zou, Beiji, Du, Jingyu, Liu, Xiyao, Wang, Yifan
Format: Artikel
Sprache:eng
Schlagworte:
Online-Zugang:Volltext
Tags: Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
container_end_page 28708
container_issue 21
container_start_page 28685
container_title Multimedia tools and applications
container_volume 77
creator Zou, Beiji
Du, Jingyu
Liu, Xiyao
Wang, Yifan
description Zero-watermarking scheme can provide durable and distortion-free digital rights management (DRM) for fundus image which plays an important role in diagnosis of ocular diseases. However, existing zero-watermarking schemes probably identify a similar fundus image as a copy, because they rarely consider the distinguishability for image. In addition, when the number of fundus images is large, it is difficult to obtain corresponding ownership shares accurately for copyright identification, because there is no retrieval mechanism in these schemes. To address these issues, a distinguishable zero-watermarking scheme which fuses similarity-based retrieval is proposed for DRM of fundus image. In our proposed scheme, distinguishable and robust features of fundus images are extracted based on the gray-scale variation. The ownership shares are constructed using visual secret sharing (VSS) by combining watermark and the master shares generated from these features. Once a suspected fundus image is found, the similarity-based retrieval is performed to retrieve the corresponding ownership share based on the feature of suspected image. After that, the copyright is identified by stacking the master share of suspected image and the retrieved ownership share. Experimental results on three public databases demonstrate that 1) Ownership shares corresponding to specific fundus images can be retrieved precisely. When fixing the false positive rate to 0.001, the mean false negative rates are not higher than 0.0693. 2) Copyrights of fundus images can be identified accurately and reliably. The mean bit error rates of recovered watermark are not higher than 0.0460.
doi_str_mv 10.1007/s11042-018-5995-4
format Article
fullrecord <record><control><sourceid>proquest_cross</sourceid><recordid>TN_cdi_proquest_journals_2033529468</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><sourcerecordid>2033529468</sourcerecordid><originalsourceid>FETCH-LOGICAL-c316t-1d7b3c63b0eefb52d05564c313f41937e54e4ddb20e3038944205b4e2bbcbe3a3</originalsourceid><addsrcrecordid>eNp1UMlOwzAQjRBIlMIHcLPE2eA1yxEVCpWKuMDZspNJ4pImxXZala_HKEicOM3TvGU0L0muKbmlhGR3nlIiGCY0x7IoJBYnyYzKjOMsY_Q0Yp4TnElCz5ML7zeE0FQyMUv2D9YH2zej9a02HaAvcAM-6ABuq91HZJAvW9gCOtjQIm-3ttPOhiM22kOFHARnYa87VA8OVbaxIWJnmzZ49KJ73URvH9BQo-XYV6NHq23cXSZnte48XP3OefK-fHxbPOP169Nqcb_GJadpwLTKDC9TbghAbSSriJSpiByvBS14BlKAqCrDCHDC80IIRqQRwIwpDXDN58nNlLtzw-cIPqjNMLo-nlSMcC5ZIdI8quikKt3gvYNa7ZyN7x8VJeqnXjXVq2K96qdeJaKHTR4ftX0D7i_5f9M3MmN_fw</addsrcrecordid><sourcetype>Aggregation Database</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype><pqid>2033529468</pqid></control><display><type>article</type><title>Distinguishable zero-watermarking scheme with similarity-based retrieval for digital rights Management of Fundus Image</title><source>SpringerLink Journals</source><creator>Zou, Beiji ; Du, Jingyu ; Liu, Xiyao ; Wang, Yifan</creator><creatorcontrib>Zou, Beiji ; Du, Jingyu ; Liu, Xiyao ; Wang, Yifan</creatorcontrib><description>Zero-watermarking scheme can provide durable and distortion-free digital rights management (DRM) for fundus image which plays an important role in diagnosis of ocular diseases. However, existing zero-watermarking schemes probably identify a similar fundus image as a copy, because they rarely consider the distinguishability for image. In addition, when the number of fundus images is large, it is difficult to obtain corresponding ownership shares accurately for copyright identification, because there is no retrieval mechanism in these schemes. To address these issues, a distinguishable zero-watermarking scheme which fuses similarity-based retrieval is proposed for DRM of fundus image. In our proposed scheme, distinguishable and robust features of fundus images are extracted based on the gray-scale variation. The ownership shares are constructed using visual secret sharing (VSS) by combining watermark and the master shares generated from these features. Once a suspected fundus image is found, the similarity-based retrieval is performed to retrieve the corresponding ownership share based on the feature of suspected image. After that, the copyright is identified by stacking the master share of suspected image and the retrieved ownership share. Experimental results on three public databases demonstrate that 1) Ownership shares corresponding to specific fundus images can be retrieved precisely. When fixing the false positive rate to 0.001, the mean false negative rates are not higher than 0.0693. 2) Copyrights of fundus images can be identified accurately and reliably. The mean bit error rates of recovered watermark are not higher than 0.0460.</description><identifier>ISSN: 1380-7501</identifier><identifier>EISSN: 1573-7721</identifier><identifier>DOI: 10.1007/s11042-018-5995-4</identifier><language>eng</language><publisher>New York: Springer US</publisher><subject>Computer Communication Networks ; Computer Science ; Copy protection ; Copyright ; Data Structures and Information Theory ; Digital imaging ; Digital rights management ; Feature extraction ; Fuses ; Multimedia Information Systems ; Ownership ; Retrieval ; Similarity ; Special Purpose and Application-Based Systems ; Watermarking</subject><ispartof>Multimedia tools and applications, 2018-11, Vol.77 (21), p.28685-28708</ispartof><rights>Springer Science+Business Media, LLC, part of Springer Nature 2018</rights><rights>Multimedia Tools and Applications is a copyright of Springer, (2018). All Rights Reserved.</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c316t-1d7b3c63b0eefb52d05564c313f41937e54e4ddb20e3038944205b4e2bbcbe3a3</citedby><cites>FETCH-LOGICAL-c316t-1d7b3c63b0eefb52d05564c313f41937e54e4ddb20e3038944205b4e2bbcbe3a3</cites><orcidid>0000-0003-2718-659X</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://link.springer.com/content/pdf/10.1007/s11042-018-5995-4$$EPDF$$P50$$Gspringer$$H</linktopdf><linktohtml>$$Uhttps://link.springer.com/10.1007/s11042-018-5995-4$$EHTML$$P50$$Gspringer$$H</linktohtml><link.rule.ids>314,776,780,27903,27904,41467,42536,51297</link.rule.ids></links><search><creatorcontrib>Zou, Beiji</creatorcontrib><creatorcontrib>Du, Jingyu</creatorcontrib><creatorcontrib>Liu, Xiyao</creatorcontrib><creatorcontrib>Wang, Yifan</creatorcontrib><title>Distinguishable zero-watermarking scheme with similarity-based retrieval for digital rights Management of Fundus Image</title><title>Multimedia tools and applications</title><addtitle>Multimed Tools Appl</addtitle><description>Zero-watermarking scheme can provide durable and distortion-free digital rights management (DRM) for fundus image which plays an important role in diagnosis of ocular diseases. However, existing zero-watermarking schemes probably identify a similar fundus image as a copy, because they rarely consider the distinguishability for image. In addition, when the number of fundus images is large, it is difficult to obtain corresponding ownership shares accurately for copyright identification, because there is no retrieval mechanism in these schemes. To address these issues, a distinguishable zero-watermarking scheme which fuses similarity-based retrieval is proposed for DRM of fundus image. In our proposed scheme, distinguishable and robust features of fundus images are extracted based on the gray-scale variation. The ownership shares are constructed using visual secret sharing (VSS) by combining watermark and the master shares generated from these features. Once a suspected fundus image is found, the similarity-based retrieval is performed to retrieve the corresponding ownership share based on the feature of suspected image. After that, the copyright is identified by stacking the master share of suspected image and the retrieved ownership share. Experimental results on three public databases demonstrate that 1) Ownership shares corresponding to specific fundus images can be retrieved precisely. When fixing the false positive rate to 0.001, the mean false negative rates are not higher than 0.0693. 2) Copyrights of fundus images can be identified accurately and reliably. The mean bit error rates of recovered watermark are not higher than 0.0460.</description><subject>Computer Communication Networks</subject><subject>Computer Science</subject><subject>Copy protection</subject><subject>Copyright</subject><subject>Data Structures and Information Theory</subject><subject>Digital imaging</subject><subject>Digital rights management</subject><subject>Feature extraction</subject><subject>Fuses</subject><subject>Multimedia Information Systems</subject><subject>Ownership</subject><subject>Retrieval</subject><subject>Similarity</subject><subject>Special Purpose and Application-Based Systems</subject><subject>Watermarking</subject><issn>1380-7501</issn><issn>1573-7721</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2018</creationdate><recordtype>article</recordtype><sourceid>8G5</sourceid><sourceid>ABUWG</sourceid><sourceid>AFKRA</sourceid><sourceid>AZQEC</sourceid><sourceid>BENPR</sourceid><sourceid>CCPQU</sourceid><sourceid>DWQXO</sourceid><sourceid>GNUQQ</sourceid><sourceid>GUQSH</sourceid><sourceid>M2O</sourceid><recordid>eNp1UMlOwzAQjRBIlMIHcLPE2eA1yxEVCpWKuMDZspNJ4pImxXZala_HKEicOM3TvGU0L0muKbmlhGR3nlIiGCY0x7IoJBYnyYzKjOMsY_Q0Yp4TnElCz5ML7zeE0FQyMUv2D9YH2zej9a02HaAvcAM-6ABuq91HZJAvW9gCOtjQIm-3ttPOhiM22kOFHARnYa87VA8OVbaxIWJnmzZ49KJ73URvH9BQo-XYV6NHq23cXSZnte48XP3OefK-fHxbPOP169Nqcb_GJadpwLTKDC9TbghAbSSriJSpiByvBS14BlKAqCrDCHDC80IIRqQRwIwpDXDN58nNlLtzw-cIPqjNMLo-nlSMcC5ZIdI8quikKt3gvYNa7ZyN7x8VJeqnXjXVq2K96qdeJaKHTR4ftX0D7i_5f9M3MmN_fw</recordid><startdate>20181101</startdate><enddate>20181101</enddate><creator>Zou, Beiji</creator><creator>Du, Jingyu</creator><creator>Liu, Xiyao</creator><creator>Wang, Yifan</creator><general>Springer US</general><general>Springer Nature B.V</general><scope>AAYXX</scope><scope>CITATION</scope><scope>3V.</scope><scope>7SC</scope><scope>7WY</scope><scope>7WZ</scope><scope>7XB</scope><scope>87Z</scope><scope>8AL</scope><scope>8AO</scope><scope>8FD</scope><scope>8FE</scope><scope>8FG</scope><scope>8FK</scope><scope>8FL</scope><scope>8G5</scope><scope>ABUWG</scope><scope>AFKRA</scope><scope>ARAPS</scope><scope>AZQEC</scope><scope>BENPR</scope><scope>BEZIV</scope><scope>BGLVJ</scope><scope>CCPQU</scope><scope>DWQXO</scope><scope>FRNLG</scope><scope>F~G</scope><scope>GNUQQ</scope><scope>GUQSH</scope><scope>HCIFZ</scope><scope>JQ2</scope><scope>K60</scope><scope>K6~</scope><scope>K7-</scope><scope>L.-</scope><scope>L7M</scope><scope>L~C</scope><scope>L~D</scope><scope>M0C</scope><scope>M0N</scope><scope>M2O</scope><scope>MBDVC</scope><scope>P5Z</scope><scope>P62</scope><scope>PQBIZ</scope><scope>PQBZA</scope><scope>PQEST</scope><scope>PQQKQ</scope><scope>PQUKI</scope><scope>PRINS</scope><scope>Q9U</scope><orcidid>https://orcid.org/0000-0003-2718-659X</orcidid></search><sort><creationdate>20181101</creationdate><title>Distinguishable zero-watermarking scheme with similarity-based retrieval for digital rights Management of Fundus Image</title><author>Zou, Beiji ; Du, Jingyu ; Liu, Xiyao ; Wang, Yifan</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c316t-1d7b3c63b0eefb52d05564c313f41937e54e4ddb20e3038944205b4e2bbcbe3a3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2018</creationdate><topic>Computer Communication Networks</topic><topic>Computer Science</topic><topic>Copy protection</topic><topic>Copyright</topic><topic>Data Structures and Information Theory</topic><topic>Digital imaging</topic><topic>Digital rights management</topic><topic>Feature extraction</topic><topic>Fuses</topic><topic>Multimedia Information Systems</topic><topic>Ownership</topic><topic>Retrieval</topic><topic>Similarity</topic><topic>Special Purpose and Application-Based Systems</topic><topic>Watermarking</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Zou, Beiji</creatorcontrib><creatorcontrib>Du, Jingyu</creatorcontrib><creatorcontrib>Liu, Xiyao</creatorcontrib><creatorcontrib>Wang, Yifan</creatorcontrib><collection>CrossRef</collection><collection>ProQuest Central (Corporate)</collection><collection>Computer and Information Systems Abstracts</collection><collection>ABI/INFORM Collection</collection><collection>ABI/INFORM Global (PDF only)</collection><collection>ProQuest Central (purchase pre-March 2016)</collection><collection>ABI/INFORM Global (Alumni Edition)</collection><collection>Computing Database (Alumni Edition)</collection><collection>ProQuest Pharma Collection</collection><collection>Technology Research Database</collection><collection>ProQuest SciTech Collection</collection><collection>ProQuest Technology Collection</collection><collection>ProQuest Central (Alumni) (purchase pre-March 2016)</collection><collection>ABI/INFORM Collection (Alumni Edition)</collection><collection>Research Library (Alumni Edition)</collection><collection>ProQuest Central (Alumni Edition)</collection><collection>ProQuest Central UK/Ireland</collection><collection>Advanced Technologies &amp; Aerospace Collection</collection><collection>ProQuest Central Essentials</collection><collection>ProQuest Central</collection><collection>Business Premium Collection</collection><collection>Technology Collection</collection><collection>ProQuest One Community College</collection><collection>ProQuest Central Korea</collection><collection>Business Premium Collection (Alumni)</collection><collection>ABI/INFORM Global (Corporate)</collection><collection>ProQuest Central Student</collection><collection>Research Library Prep</collection><collection>SciTech Premium Collection</collection><collection>ProQuest Computer Science Collection</collection><collection>ProQuest Business Collection (Alumni Edition)</collection><collection>ProQuest Business Collection</collection><collection>Computer Science Database</collection><collection>ABI/INFORM Professional Advanced</collection><collection>Advanced Technologies Database with Aerospace</collection><collection>Computer and Information Systems Abstracts – Academic</collection><collection>Computer and Information Systems Abstracts Professional</collection><collection>ABI/INFORM Global</collection><collection>Computing Database</collection><collection>Research Library</collection><collection>Research Library (Corporate)</collection><collection>Advanced Technologies &amp; Aerospace Database</collection><collection>ProQuest Advanced Technologies &amp; Aerospace Collection</collection><collection>ProQuest One Business</collection><collection>ProQuest One Business (Alumni)</collection><collection>ProQuest One Academic Eastern Edition (DO NOT USE)</collection><collection>ProQuest One Academic</collection><collection>ProQuest One Academic UKI Edition</collection><collection>ProQuest Central China</collection><collection>ProQuest Central Basic</collection><jtitle>Multimedia tools and applications</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Zou, Beiji</au><au>Du, Jingyu</au><au>Liu, Xiyao</au><au>Wang, Yifan</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Distinguishable zero-watermarking scheme with similarity-based retrieval for digital rights Management of Fundus Image</atitle><jtitle>Multimedia tools and applications</jtitle><stitle>Multimed Tools Appl</stitle><date>2018-11-01</date><risdate>2018</risdate><volume>77</volume><issue>21</issue><spage>28685</spage><epage>28708</epage><pages>28685-28708</pages><issn>1380-7501</issn><eissn>1573-7721</eissn><abstract>Zero-watermarking scheme can provide durable and distortion-free digital rights management (DRM) for fundus image which plays an important role in diagnosis of ocular diseases. However, existing zero-watermarking schemes probably identify a similar fundus image as a copy, because they rarely consider the distinguishability for image. In addition, when the number of fundus images is large, it is difficult to obtain corresponding ownership shares accurately for copyright identification, because there is no retrieval mechanism in these schemes. To address these issues, a distinguishable zero-watermarking scheme which fuses similarity-based retrieval is proposed for DRM of fundus image. In our proposed scheme, distinguishable and robust features of fundus images are extracted based on the gray-scale variation. The ownership shares are constructed using visual secret sharing (VSS) by combining watermark and the master shares generated from these features. Once a suspected fundus image is found, the similarity-based retrieval is performed to retrieve the corresponding ownership share based on the feature of suspected image. After that, the copyright is identified by stacking the master share of suspected image and the retrieved ownership share. Experimental results on three public databases demonstrate that 1) Ownership shares corresponding to specific fundus images can be retrieved precisely. When fixing the false positive rate to 0.001, the mean false negative rates are not higher than 0.0693. 2) Copyrights of fundus images can be identified accurately and reliably. The mean bit error rates of recovered watermark are not higher than 0.0460.</abstract><cop>New York</cop><pub>Springer US</pub><doi>10.1007/s11042-018-5995-4</doi><tpages>24</tpages><orcidid>https://orcid.org/0000-0003-2718-659X</orcidid></addata></record>
fulltext fulltext
identifier ISSN: 1380-7501
ispartof Multimedia tools and applications, 2018-11, Vol.77 (21), p.28685-28708
issn 1380-7501
1573-7721
language eng
recordid cdi_proquest_journals_2033529468
source SpringerLink Journals
subjects Computer Communication Networks
Computer Science
Copy protection
Copyright
Data Structures and Information Theory
Digital imaging
Digital rights management
Feature extraction
Fuses
Multimedia Information Systems
Ownership
Retrieval
Similarity
Special Purpose and Application-Based Systems
Watermarking
title Distinguishable zero-watermarking scheme with similarity-based retrieval for digital rights Management of Fundus Image
url https://sfx.bib-bvb.de/sfx_tum?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2025-01-26T05%3A59%3A22IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-proquest_cross&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.genre=article&rft.atitle=Distinguishable%20zero-watermarking%20scheme%20with%20similarity-based%20retrieval%20for%20digital%20rights%20Management%20of%20Fundus%20Image&rft.jtitle=Multimedia%20tools%20and%20applications&rft.au=Zou,%20Beiji&rft.date=2018-11-01&rft.volume=77&rft.issue=21&rft.spage=28685&rft.epage=28708&rft.pages=28685-28708&rft.issn=1380-7501&rft.eissn=1573-7721&rft_id=info:doi/10.1007/s11042-018-5995-4&rft_dat=%3Cproquest_cross%3E2033529468%3C/proquest_cross%3E%3Curl%3E%3C/url%3E&disable_directlink=true&sfx.directlink=off&sfx.report_link=0&rft_id=info:oai/&rft_pqid=2033529468&rft_id=info:pmid/&rfr_iscdi=true