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231225s2021 xx |||||o 00| ||eng c |
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|a 10.1109/TIP.2020.3037524
|2 doi
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|a DE-627
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|a eng
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| 100 |
1 |
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|a Barron, Irving
|e verfasserin
|4 aut
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| 245 |
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|a Dual Modulated QR Codes for Proximal Privacy and Security
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|c 2021
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|a Text
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|2 rdacontent
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|a ƒaComputermedien
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|2 rdamedia
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|a ƒa Online-Ressource
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|a Date Revised 07.12.2020
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|a published: Print-Electronic
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|a Citation Status PubMed-not-MEDLINE
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|a The ubiquitous presence of surveillance cameras severely compromises the security of private information (e.g. passwords) entered via a conventional keyboard interface in public places. We address this problem by proposing dual modulated QR (DMQR) codes, a novel QR code extension via which users can securely communicate private information in public places using their smartphones and a camera interface. Dual modulated QR codes use the same synchronization patterns and module geometry as conventional monochrome QR codes. Within each module, primary data is embedded using intensity modulation compatible with conventional QR code decoding. Specifically, depending on the bit to be embedded, a module is either left white or an elliptical black dot is placed within it. Additionally, for each module containing an elliptical dot, secondary data is embedded by orientation modulation; that is, by using different orientations for the elliptical dots. Because the orientation of the elliptical dots can only be reliably assessed when the barcodes are captured from a close distance, the secondary data provides "proximal privacy" and can be effectively used to communicate private information securely in public settings. Tests conducted using several alternative parameter settings demonstrate that the proposed DMQR codes are effective in meeting their objective- the secondary data can be accurately decoded for short capture distances (6 in.) but cannot be recovered from images captured over long distances (>12 in.). Furthermore, the proximal privacy can be adapted to application needs by varying the eccentricity of the elliptical dots used
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|a Journal Article
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1 |
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|a Yeh, Hsin Jui
|e verfasserin
|4 aut
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| 700 |
1 |
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|a Dinesh, Karthik
|e verfasserin
|4 aut
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| 700 |
1 |
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|a Sharma, Gaurav
|e verfasserin
|4 aut
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| 773 |
0 |
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|i Enthalten in
|t IEEE transactions on image processing : a publication of the IEEE Signal Processing Society
|d 1992
|g 30(2021) vom: 21., Seite 657-669
|w (DE-627)NLM09821456X
|x 1941-0042
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| 773 |
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|g volume:30
|g year:2021
|g day:21
|g pages:657-669
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|u http://dx.doi.org/10.1109/TIP.2020.3037524
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