Micrography QR Codes
This paper presents a novel algorithm to generate micrography QR codes , a novel machine-readable graphic generated by embedding a QR code within a micrography image. The unique structure of micrography makes it incompatible with existing methods used to combine QR codes with natural or halftone ima...
Gespeichert in:
Veröffentlicht in: | IEEE transactions on visualization and computer graphics 2020-09, Vol.26 (9), p.2834-2847 |
---|---|
Hauptverfasser: | , , , , , , |
Format: | Artikel |
Sprache: | eng |
Schlagworte: | |
Online-Zugang: | Volltext bestellen |
Tags: |
Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
|
container_end_page | 2847 |
---|---|
container_issue | 9 |
container_start_page | 2834 |
container_title | IEEE transactions on visualization and computer graphics |
container_volume | 26 |
creator | Hung, Shih-Hsuan Yao, Chih-Yuan Fang, Yu-Jen Tan, Ping Lee, Ruen-Rone Sheffer, Alla Chu, Hung-Kuo |
description | This paper presents a novel algorithm to generate micrography QR codes , a novel machine-readable graphic generated by embedding a QR code within a micrography image. The unique structure of micrography makes it incompatible with existing methods used to combine QR codes with natural or halftone images. We exploited the high-frequency nature of micrography in the design of a novel deformation model that enables the skillful warping of individual letters and adjustment of font weights to enable the embedding of a QR code within a micrography. The entire process is supervised by a set of visual quality metrics tailored specifically for micrography, in conjunction with a novel QR code quality measure aimed at striking a balance between visual fidelity and decoding robustness. The proposed QR code quality measure is based on probabilistic models learned from decoding experiments using popular decoders with synthetic QR codes to capture the various forms of distortion that result from image embedding. Experiment results demonstrate the efficacy of the proposed method in generating micrography QR codes of high quality from a wide variety of inputs. The ability to embed QR codes with multiple scales makes it possible to produce a wide range of diverse designs. Experiments and user studies were conducted to evaluate the proposed method from a qualitative as well as quantitative perspective. |
doi_str_mv | 10.1109/TVCG.2019.2896895 |
format | Article |
fullrecord | <record><control><sourceid>proquest_RIE</sourceid><recordid>TN_cdi_proquest_miscellaneous_2179508082</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><ieee_id>8632711</ieee_id><sourcerecordid>2429225297</sourcerecordid><originalsourceid>FETCH-LOGICAL-c349t-25b8de72e9c014326cf0817701e9146bc206bc1adb3a81380449f43ff410de913</originalsourceid><addsrcrecordid>eNpdkE1LAzEQhoMoVqs3LyJIwYuXrTOTbD6OsmgVKqJUr2E_srql7dake-i_N6W1By9JIM_7MvMwdokwRARzN_nMRkMCNEPSRmqTHrATNAITSEEexjcolZAk2WOnIUwBUAhtjlmPg0IJXJ-wi5em9O2Xz5ff68Hb-yBrKxfO2FGdz4I739199vH4MMmekvHr6Dm7HyclF2aVUFroyilypozNnGRZg0alAJ1BIYuSIB6YVwXPNXINQpha8LoWCFVEeJ_dbnuXvv3pXFjZeRNKN5vlC9d2wRIqk4IGTRG9-YdO284v4nSWBBmilIyKFG6puFMI3tV26Zt57tcWwW6U2Y0yu1Fmd8pi5nrX3BVzV-0Tf44icLUFGufc_ltLTgqR_wLMI2tt</addsrcrecordid><sourcetype>Aggregation Database</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype><pqid>2429225297</pqid></control><display><type>article</type><title>Micrography QR Codes</title><source>IEEE Electronic Library (IEL)</source><creator>Hung, Shih-Hsuan ; Yao, Chih-Yuan ; Fang, Yu-Jen ; Tan, Ping ; Lee, Ruen-Rone ; Sheffer, Alla ; Chu, Hung-Kuo</creator><creatorcontrib>Hung, Shih-Hsuan ; Yao, Chih-Yuan ; Fang, Yu-Jen ; Tan, Ping ; Lee, Ruen-Rone ; Sheffer, Alla ; Chu, Hung-Kuo</creatorcontrib><description>This paper presents a novel algorithm to generate micrography QR codes , a novel machine-readable graphic generated by embedding a QR code within a micrography image. The unique structure of micrography makes it incompatible with existing methods used to combine QR codes with natural or halftone images. We exploited the high-frequency nature of micrography in the design of a novel deformation model that enables the skillful warping of individual letters and adjustment of font weights to enable the embedding of a QR code within a micrography. The entire process is supervised by a set of visual quality metrics tailored specifically for micrography, in conjunction with a novel QR code quality measure aimed at striking a balance between visual fidelity and decoding robustness. The proposed QR code quality measure is based on probabilistic models learned from decoding experiments using popular decoders with synthetic QR codes to capture the various forms of distortion that result from image embedding. Experiment results demonstrate the efficacy of the proposed method in generating micrography QR codes of high quality from a wide variety of inputs. The ability to embed QR codes with multiple scales makes it possible to produce a wide range of diverse designs. Experiments and user studies were conducted to evaluate the proposed method from a qualitative as well as quantitative perspective.</description><identifier>ISSN: 1077-2626</identifier><identifier>EISSN: 1941-0506</identifier><identifier>DOI: 10.1109/TVCG.2019.2896895</identifier><identifier>PMID: 30716038</identifier><identifier>CODEN: ITVGEA</identifier><language>eng</language><publisher>United States: IEEE</publisher><subject>Algorithms ; Codes ; Decoders ; Decoding ; Distortion ; Distortion measurement ; Embedding ; Encoding ; image warping ; Micrography ; Optimization ; Probabilistic models ; QR code ; Strain ; typography ; Visualization</subject><ispartof>IEEE transactions on visualization and computer graphics, 2020-09, Vol.26 (9), p.2834-2847</ispartof><rights>Copyright The Institute of Electrical and Electronics Engineers, Inc. (IEEE) 2020</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c349t-25b8de72e9c014326cf0817701e9146bc206bc1adb3a81380449f43ff410de913</citedby><cites>FETCH-LOGICAL-c349t-25b8de72e9c014326cf0817701e9146bc206bc1adb3a81380449f43ff410de913</cites><orcidid>0000-0002-6435-9464 ; 0000-0002-0368-3973 ; 0000-0002-4506-6973 ; 0000-0003-4487-8483 ; 0000-0001-6608-7178</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://ieeexplore.ieee.org/document/8632711$$EHTML$$P50$$Gieee$$H</linktohtml><link.rule.ids>314,776,780,792,27901,27902,54733</link.rule.ids><linktorsrc>$$Uhttps://ieeexplore.ieee.org/document/8632711$$EView_record_in_IEEE$$FView_record_in_$$GIEEE</linktorsrc><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/30716038$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Hung, Shih-Hsuan</creatorcontrib><creatorcontrib>Yao, Chih-Yuan</creatorcontrib><creatorcontrib>Fang, Yu-Jen</creatorcontrib><creatorcontrib>Tan, Ping</creatorcontrib><creatorcontrib>Lee, Ruen-Rone</creatorcontrib><creatorcontrib>Sheffer, Alla</creatorcontrib><creatorcontrib>Chu, Hung-Kuo</creatorcontrib><title>Micrography QR Codes</title><title>IEEE transactions on visualization and computer graphics</title><addtitle>TVCG</addtitle><addtitle>IEEE Trans Vis Comput Graph</addtitle><description>This paper presents a novel algorithm to generate micrography QR codes , a novel machine-readable graphic generated by embedding a QR code within a micrography image. The unique structure of micrography makes it incompatible with existing methods used to combine QR codes with natural or halftone images. We exploited the high-frequency nature of micrography in the design of a novel deformation model that enables the skillful warping of individual letters and adjustment of font weights to enable the embedding of a QR code within a micrography. The entire process is supervised by a set of visual quality metrics tailored specifically for micrography, in conjunction with a novel QR code quality measure aimed at striking a balance between visual fidelity and decoding robustness. The proposed QR code quality measure is based on probabilistic models learned from decoding experiments using popular decoders with synthetic QR codes to capture the various forms of distortion that result from image embedding. Experiment results demonstrate the efficacy of the proposed method in generating micrography QR codes of high quality from a wide variety of inputs. The ability to embed QR codes with multiple scales makes it possible to produce a wide range of diverse designs. Experiments and user studies were conducted to evaluate the proposed method from a qualitative as well as quantitative perspective.</description><subject>Algorithms</subject><subject>Codes</subject><subject>Decoders</subject><subject>Decoding</subject><subject>Distortion</subject><subject>Distortion measurement</subject><subject>Embedding</subject><subject>Encoding</subject><subject>image warping</subject><subject>Micrography</subject><subject>Optimization</subject><subject>Probabilistic models</subject><subject>QR code</subject><subject>Strain</subject><subject>typography</subject><subject>Visualization</subject><issn>1077-2626</issn><issn>1941-0506</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2020</creationdate><recordtype>article</recordtype><sourceid>RIE</sourceid><recordid>eNpdkE1LAzEQhoMoVqs3LyJIwYuXrTOTbD6OsmgVKqJUr2E_srql7dake-i_N6W1By9JIM_7MvMwdokwRARzN_nMRkMCNEPSRmqTHrATNAITSEEexjcolZAk2WOnIUwBUAhtjlmPg0IJXJ-wi5em9O2Xz5ff68Hb-yBrKxfO2FGdz4I739199vH4MMmekvHr6Dm7HyclF2aVUFroyilypozNnGRZg0alAJ1BIYuSIB6YVwXPNXINQpha8LoWCFVEeJ_dbnuXvv3pXFjZeRNKN5vlC9d2wRIqk4IGTRG9-YdO284v4nSWBBmilIyKFG6puFMI3tV26Zt57tcWwW6U2Y0yu1Fmd8pi5nrX3BVzV-0Tf44icLUFGufc_ltLTgqR_wLMI2tt</recordid><startdate>20200901</startdate><enddate>20200901</enddate><creator>Hung, Shih-Hsuan</creator><creator>Yao, Chih-Yuan</creator><creator>Fang, Yu-Jen</creator><creator>Tan, Ping</creator><creator>Lee, Ruen-Rone</creator><creator>Sheffer, Alla</creator><creator>Chu, Hung-Kuo</creator><general>IEEE</general><general>The Institute of Electrical and Electronics Engineers, Inc. (IEEE)</general><scope>97E</scope><scope>RIA</scope><scope>RIE</scope><scope>NPM</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>7SC</scope><scope>7SP</scope><scope>8FD</scope><scope>JQ2</scope><scope>L7M</scope><scope>L~C</scope><scope>L~D</scope><scope>7X8</scope><orcidid>https://orcid.org/0000-0002-6435-9464</orcidid><orcidid>https://orcid.org/0000-0002-0368-3973</orcidid><orcidid>https://orcid.org/0000-0002-4506-6973</orcidid><orcidid>https://orcid.org/0000-0003-4487-8483</orcidid><orcidid>https://orcid.org/0000-0001-6608-7178</orcidid></search><sort><creationdate>20200901</creationdate><title>Micrography QR Codes</title><author>Hung, Shih-Hsuan ; Yao, Chih-Yuan ; Fang, Yu-Jen ; Tan, Ping ; Lee, Ruen-Rone ; Sheffer, Alla ; Chu, Hung-Kuo</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c349t-25b8de72e9c014326cf0817701e9146bc206bc1adb3a81380449f43ff410de913</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2020</creationdate><topic>Algorithms</topic><topic>Codes</topic><topic>Decoders</topic><topic>Decoding</topic><topic>Distortion</topic><topic>Distortion measurement</topic><topic>Embedding</topic><topic>Encoding</topic><topic>image warping</topic><topic>Micrography</topic><topic>Optimization</topic><topic>Probabilistic models</topic><topic>QR code</topic><topic>Strain</topic><topic>typography</topic><topic>Visualization</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Hung, Shih-Hsuan</creatorcontrib><creatorcontrib>Yao, Chih-Yuan</creatorcontrib><creatorcontrib>Fang, Yu-Jen</creatorcontrib><creatorcontrib>Tan, Ping</creatorcontrib><creatorcontrib>Lee, Ruen-Rone</creatorcontrib><creatorcontrib>Sheffer, Alla</creatorcontrib><creatorcontrib>Chu, Hung-Kuo</creatorcontrib><collection>IEEE All-Society Periodicals Package (ASPP) 2005-present</collection><collection>IEEE All-Society Periodicals Package (ASPP) 1998-Present</collection><collection>IEEE Electronic Library (IEL)</collection><collection>PubMed</collection><collection>CrossRef</collection><collection>Computer and Information Systems Abstracts</collection><collection>Electronics & Communications Abstracts</collection><collection>Technology Research Database</collection><collection>ProQuest Computer Science Collection</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>MEDLINE - Academic</collection><jtitle>IEEE transactions on visualization and computer graphics</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext_linktorsrc</fulltext></delivery><addata><au>Hung, Shih-Hsuan</au><au>Yao, Chih-Yuan</au><au>Fang, Yu-Jen</au><au>Tan, Ping</au><au>Lee, Ruen-Rone</au><au>Sheffer, Alla</au><au>Chu, Hung-Kuo</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Micrography QR Codes</atitle><jtitle>IEEE transactions on visualization and computer graphics</jtitle><stitle>TVCG</stitle><addtitle>IEEE Trans Vis Comput Graph</addtitle><date>2020-09-01</date><risdate>2020</risdate><volume>26</volume><issue>9</issue><spage>2834</spage><epage>2847</epage><pages>2834-2847</pages><issn>1077-2626</issn><eissn>1941-0506</eissn><coden>ITVGEA</coden><abstract>This paper presents a novel algorithm to generate micrography QR codes , a novel machine-readable graphic generated by embedding a QR code within a micrography image. The unique structure of micrography makes it incompatible with existing methods used to combine QR codes with natural or halftone images. We exploited the high-frequency nature of micrography in the design of a novel deformation model that enables the skillful warping of individual letters and adjustment of font weights to enable the embedding of a QR code within a micrography. The entire process is supervised by a set of visual quality metrics tailored specifically for micrography, in conjunction with a novel QR code quality measure aimed at striking a balance between visual fidelity and decoding robustness. The proposed QR code quality measure is based on probabilistic models learned from decoding experiments using popular decoders with synthetic QR codes to capture the various forms of distortion that result from image embedding. Experiment results demonstrate the efficacy of the proposed method in generating micrography QR codes of high quality from a wide variety of inputs. The ability to embed QR codes with multiple scales makes it possible to produce a wide range of diverse designs. Experiments and user studies were conducted to evaluate the proposed method from a qualitative as well as quantitative perspective.</abstract><cop>United States</cop><pub>IEEE</pub><pmid>30716038</pmid><doi>10.1109/TVCG.2019.2896895</doi><tpages>14</tpages><orcidid>https://orcid.org/0000-0002-6435-9464</orcidid><orcidid>https://orcid.org/0000-0002-0368-3973</orcidid><orcidid>https://orcid.org/0000-0002-4506-6973</orcidid><orcidid>https://orcid.org/0000-0003-4487-8483</orcidid><orcidid>https://orcid.org/0000-0001-6608-7178</orcidid></addata></record> |
fulltext | fulltext_linktorsrc |
identifier | ISSN: 1077-2626 |
ispartof | IEEE transactions on visualization and computer graphics, 2020-09, Vol.26 (9), p.2834-2847 |
issn | 1077-2626 1941-0506 |
language | eng |
recordid | cdi_proquest_miscellaneous_2179508082 |
source | IEEE Electronic Library (IEL) |
subjects | Algorithms Codes Decoders Decoding Distortion Distortion measurement Embedding Encoding image warping Micrography Optimization Probabilistic models QR code Strain typography Visualization |
title | Micrography QR Codes |
url | https://sfx.bib-bvb.de/sfx_tum?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2025-02-03T17%3A13%3A55IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-proquest_RIE&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.genre=article&rft.atitle=Micrography%20QR%20Codes&rft.jtitle=IEEE%20transactions%20on%20visualization%20and%20computer%20graphics&rft.au=Hung,%20Shih-Hsuan&rft.date=2020-09-01&rft.volume=26&rft.issue=9&rft.spage=2834&rft.epage=2847&rft.pages=2834-2847&rft.issn=1077-2626&rft.eissn=1941-0506&rft.coden=ITVGEA&rft_id=info:doi/10.1109/TVCG.2019.2896895&rft_dat=%3Cproquest_RIE%3E2429225297%3C/proquest_RIE%3E%3Curl%3E%3C/url%3E&disable_directlink=true&sfx.directlink=off&sfx.report_link=0&rft_id=info:oai/&rft_pqid=2429225297&rft_id=info:pmid/30716038&rft_ieee_id=8632711&rfr_iscdi=true |