research-article

QR Code Detection Based on Local Features

Authors:

Feng DaiAuthors Info & Claims

ICIMCS '14: Proceedings of International Conference on Internet Multimedia Computing and Service

Pages 319 - 322

https://doi.org/10.1145/2632856.2632860

Published: 10 July 2014 Publication History

Abstract

2D barcode detection is the initial step for barcode content identification, which is critical for its wide application. A great deal of effort has been made in recent years to develop 2D barcode detection methods. However, less attention has been paid to locate 2D barcode within large background areas. In this paper, a QR (Quick Response) 2D barcode detection method is proposed, which utilizes LBP (Local Binary Pattern) and image contour features. Experiments demonstrate the superior detection accuracy and speed of the method.

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Cited By

Gu WSun LJiang ZSun K(2024)High-Performance Embedded System Design for QR Code Recognition With Deep LearningIEEE MultiMedia10.1109/MMUL.2024.345900331:4(70-78)Online publication date: Oct-2024
https://doi.org/10.1109/MMUL.2024.3459003
Lam KSum K(2023)An FPGA-Friendly Algorithm for QR Code Detection2023 IEEE International Symposium on Circuits and Systems (ISCAS)10.1109/ISCAS46773.2023.10181737(1-5)Online publication date: 21-May-2023
https://doi.org/10.1109/ISCAS46773.2023.10181737
Blanger LHirata N(2019)An Evaluation of Deep Learning Techniques for Qr Code Detection2019 IEEE International Conference on Image Processing (ICIP)10.1109/ICIP.2019.8803075(1625-1629)Online publication date: Sep-2019
https://doi.org/10.1109/ICIP.2019.8803075
Show More Cited By

Index Terms

QR Code Detection Based on Local Features
1. Computing methodologies
  1. Artificial intelligence
    1. Computer vision

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Published In

cover image ACM Other conferences

ICIMCS '14: Proceedings of International Conference on Internet Multimedia Computing and Service

July 2014

430 pages

ISBN:9781450328104

DOI:10.1145/2632856

General Chairs:
Hanzi Wang
Xiamen University, China
,
Larry Davis
University of Maryland, USA
,
Program Chairs:
Wenwu Zhu
Tsinghua University, China
,
Stephan Kopf
University of Mannheim, Germany
,
Yanyun Qu
Xiamen University, China
,
Publications Chairs:
Jun Yu
Xiamen University, China
,
Jitao Sang
Institute of Automation, CAS, China
,
Tao Mei
Microsoft Research Asia, China

Copyright © 2014 ACM.

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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NSF of China: National Natural Science Foundation of China
Beijing ACM SIGMM Chapter

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 10 July 2014

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ICIMCS '14

ICIMCS '14: International Conference on Internet Multimedia Computing and Service

July 10 - 12, 2014

Xiamen, China

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Overall Acceptance Rate 163 of 456 submissions, 36%

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Cited By

Gu WSun LJiang ZSun K(2024)High-Performance Embedded System Design for QR Code Recognition With Deep LearningIEEE MultiMedia10.1109/MMUL.2024.345900331:4(70-78)Online publication date: Oct-2024
https://doi.org/10.1109/MMUL.2024.3459003
Lam KSum K(2023)An FPGA-Friendly Algorithm for QR Code Detection2023 IEEE International Symposium on Circuits and Systems (ISCAS)10.1109/ISCAS46773.2023.10181737(1-5)Online publication date: 21-May-2023
https://doi.org/10.1109/ISCAS46773.2023.10181737
Blanger LHirata N(2019)An Evaluation of Deep Learning Techniques for Qr Code Detection2019 IEEE International Conference on Image Processing (ICIP)10.1109/ICIP.2019.8803075(1625-1629)Online publication date: Sep-2019
https://doi.org/10.1109/ICIP.2019.8803075
Tian SZhang LMorin LDeforges O(2018)SC-IQA: Shift compensation based image quality assessment for DIBR-synthesized views2018 IEEE Visual Communications and Image Processing (VCIP)10.1109/VCIP.2018.8698654(1-4)Online publication date: Dec-2018
https://doi.org/10.1109/VCIP.2018.8698654
Tian YChe ZZhai GGao Z(2018)BAN, A Barcode Accurate Detection Network2018 IEEE Visual Communications and Image Processing (VCIP)10.1109/VCIP.2018.8698633(1-5)Online publication date: Dec-2018
https://doi.org/10.1109/VCIP.2018.8698633
Jian-bo CPeng CDa-zhong MMu-ming LJing W(2016)Study on macro control technology of mobile phone imaging2016 IEEE Optoelectronics Global Conference (OGC)10.1109/OGC.2016.7590481(1-4)Online publication date: Sep-2016
https://doi.org/10.1109/OGC.2016.7590481

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