Evidence map›Paper›PMID 32878171›Full record

ArticleSensors (Basel, Switzerland)2020

Customized 2D Barcode Sensing for Anti-Counterfeiting Application in Smart IoT with Fast Encoding and Information Hiding.

Rongjun Chen, Yongxing Yu, Jiangtao Chen, Yongbin Zhong, Huimin Zhao, Amir Hussain, Hong-Zhou Tan

Abstract read
In one paragraph

Article in Sensors (Basel, Switzerland), 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

7 authors.

Rongjun ChenSchool of Computer Science, Guangdong Polytechnic Normal University, Guangzhou 510665, China.
Yongxing YuSchool of Computer Science, Guangdong Polytechnic Normal University, Guangzhou 510665, China.ORCID 0000-0002-9559-1880
Jiangtao ChenSchool of Electrics and Information Technology, Sun Yat-sen University, Guangzhou 510006, China.
Yongbin ZhongSchool of Electrics and Information Technology, Sun Yat-sen University, Guangzhou 510006, China.
Huimin ZhaoSchool of Computer Science, Guangdong Polytechnic Normal University, Guangzhou 510665, China.
Amir HussainSchool of Computing, Edinburgh Napier University, Edinburgh EH10 5DT, UK.ORCID 0000-0002-8080-082X
Hong-Zhou TanSchool of Electrics and Information Technology, Sun Yat-sen University, Guangzhou 510006, China.

Funding

the Guangdong Colleges and Universities Young Innovative Talents Projects NO. 2018KQNCX138the Innovation Team Project of the Education Department of Guangdong Province NO.2017KCXTD021the National Natural Science Foundation of China NO.61672008the Ph.D. Start-up Fund of Natural Science Foundation of Guangdong Province NO.2016A030310335the Project for Distinctive Innovation of Ordinary Universities of Guangdong Province NO.2018KTSCX120the Science and Technology Planning Project of Guangdong Province NO.76120-42020022
6 · The paper itself

Abstract

With the development of commodity economy, the emergence of fake and shoddy products has seriously harmed the interests of consumers and enterprises. To tackle this challenge, customized 2D barcode is proposed to satisfy the requirements of the enterprise anti-counterfeiting certification. Based on information hiding technology, the proposed approach can solve these challenging problems and provide a low-cost, difficult to forge, and easy to identify solution, while achieving the function of conventional 2D barcodes. By weighting between the perceptual quality and decoding robustness in sensing recognition, the customized 2D barcode can maintain a better aesthetic appearance for anti-counterfeiting and achieve fast encoding. A new picture-embedding scheme was designed to consider 2D barcode, within a unit image block as a basic encoding unit, where the 2D barcode finder patterns were embedded after encoding. Experimental results demonstrated that the proposed customized barcode could provide better encoding characteristics, while maintaining better decoding robustness than several state-of-the-art methods. Additionally, as a closed source 2D barcode that could be visually anti-counterfeit, the customized 2D barcode could effectively prevent counterfeiting that replicate physical labels. Benefitting from the high-security, high information capacity, and low-cost, the proposed customized 2D barcode with sensing recognition scheme provide a highly practical, valuable in terms of marketing, and anti-counterfeiting traceable solution for future smart IoT applications.

Indexed as

2D barcodeanti-counterfeitinginformation hidingperceptual quality

Identifiers

PMID32878171
PMCPMC7506946

What OpenQuestion holds

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LicenceCC BY
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Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.