A new QR Code Recognition Method using Deblurring and Modified Local Adaptive Thresholding Techniques

Junnian Li; Biao Hu; Zhengcai Cao

doi:10.1109/CASE48305.2020.9216945

A new QR Code Recognition Method using Deblurring and Modified Local Adaptive Thresholding Techniques

Junnian Li
, Biao Hu
, Zhengcai Cao^*

^*Corresponding author for this work

Beijing University of Chemical Technology

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

7 Scopus citations

Abstract

Quick Response (QR) Code would be easily affected by motion blur. In this study, a new recognition method for blurry QR Code is presented. First, a motion deblurring algorithm based on generative adversarial networks (GAN) is applied to perform the blind motion deblurring on single QR Code image for improving the quality of QR Code pictures. Then a modified local adaptive thresholding algorithm applying integral image technology is utilized in order to acquire binary QR Code pictures. Finally, this algorithm would be compared with some previous methods. Furthermore, for testing this algorithm, a database which contains motion blurry QR Code images from both public database and real scenes is collected. Experimental results show that this proposed algorithm perform well on motion blurry QR Code recognition missions.

Original language	English
Title of host publication	2020 IEEE 16th International Conference on Automation Science and Engineering, CASE 2020
Publisher	IEEE Computer Society
Pages	1269-1274
Number of pages	6
ISBN (Electronic)	9781728169040
DOIs	https://doi.org/10.1109/CASE48305.2020.9216945
State	Published - Aug 2020
Externally published	Yes
Event	16th IEEE International Conference on Automation Science and Engineering, CASE 2020 - Hong Kong, Hong Kong Duration: 20 Aug 2020 → 21 Aug 2020

Publication series

Name	IEEE International Conference on Automation Science and Engineering
Volume	2020-August
ISSN (Print)	2161-8070
ISSN (Electronic)	2161-8089

Conference

Conference	16th IEEE International Conference on Automation Science and Engineering, CASE 2020
Country/Territory	Hong Kong
City	Hong Kong
Period	20/08/20 → 21/08/20

Access to Document

10.1109/CASE48305.2020.9216945

Cite this

Li, J., Hu, B., & Cao, Z. (2020). A new QR Code Recognition Method using Deblurring and Modified Local Adaptive Thresholding Techniques. In 2020 IEEE 16th International Conference on Automation Science and Engineering, CASE 2020 (pp. 1269-1274). Article 9216945 (IEEE International Conference on Automation Science and Engineering; Vol. 2020-August). IEEE Computer Society. https://doi.org/10.1109/CASE48305.2020.9216945

@inproceedings{150b430858934478aab8f10df012a931,

title = "A new QR Code Recognition Method using Deblurring and Modified Local Adaptive Thresholding Techniques",

abstract = "Quick Response (QR) Code would be easily affected by motion blur. In this study, a new recognition method for blurry QR Code is presented. First, a motion deblurring algorithm based on generative adversarial networks (GAN) is applied to perform the blind motion deblurring on single QR Code image for improving the quality of QR Code pictures. Then a modified local adaptive thresholding algorithm applying integral image technology is utilized in order to acquire binary QR Code pictures. Finally, this algorithm would be compared with some previous methods. Furthermore, for testing this algorithm, a database which contains motion blurry QR Code images from both public database and real scenes is collected. Experimental results show that this proposed algorithm perform well on motion blurry QR Code recognition missions.",

author = "Junnian Li and Biao Hu and Zhengcai Cao",

note = "Publisher Copyright: {\textcopyright} 2020 IEEE.; 16th IEEE International Conference on Automation Science and Engineering, CASE 2020 ; Conference date: 20-08-2020 Through 21-08-2020",

year = "2020",

month = aug,

doi = "10.1109/CASE48305.2020.9216945",

language = "英语",

series = "IEEE International Conference on Automation Science and Engineering",

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pages = "1269--1274",

booktitle = "2020 IEEE 16th International Conference on Automation Science and Engineering, CASE 2020",

address = "美国",

}

Li, J, Hu, B & Cao, Z 2020, A new QR Code Recognition Method using Deblurring and Modified Local Adaptive Thresholding Techniques. in 2020 IEEE 16th International Conference on Automation Science and Engineering, CASE 2020., 9216945, IEEE International Conference on Automation Science and Engineering, vol. 2020-August, IEEE Computer Society, pp. 1269-1274, 16th IEEE International Conference on Automation Science and Engineering, CASE 2020, Hong Kong, Hong Kong, 20/08/20. https://doi.org/10.1109/CASE48305.2020.9216945

A new QR Code Recognition Method using Deblurring and Modified Local Adaptive Thresholding Techniques. / Li, Junnian; Hu, Biao; Cao, Zhengcai.
2020 IEEE 16th International Conference on Automation Science and Engineering, CASE 2020. IEEE Computer Society, 2020. p. 1269-1274 9216945 (IEEE International Conference on Automation Science and Engineering; Vol. 2020-August).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

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N2 - Quick Response (QR) Code would be easily affected by motion blur. In this study, a new recognition method for blurry QR Code is presented. First, a motion deblurring algorithm based on generative adversarial networks (GAN) is applied to perform the blind motion deblurring on single QR Code image for improving the quality of QR Code pictures. Then a modified local adaptive thresholding algorithm applying integral image technology is utilized in order to acquire binary QR Code pictures. Finally, this algorithm would be compared with some previous methods. Furthermore, for testing this algorithm, a database which contains motion blurry QR Code images from both public database and real scenes is collected. Experimental results show that this proposed algorithm perform well on motion blurry QR Code recognition missions.

AB - Quick Response (QR) Code would be easily affected by motion blur. In this study, a new recognition method for blurry QR Code is presented. First, a motion deblurring algorithm based on generative adversarial networks (GAN) is applied to perform the blind motion deblurring on single QR Code image for improving the quality of QR Code pictures. Then a modified local adaptive thresholding algorithm applying integral image technology is utilized in order to acquire binary QR Code pictures. Finally, this algorithm would be compared with some previous methods. Furthermore, for testing this algorithm, a database which contains motion blurry QR Code images from both public database and real scenes is collected. Experimental results show that this proposed algorithm perform well on motion blurry QR Code recognition missions.

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Li J, Hu B, Cao Z. A new QR Code Recognition Method using Deblurring and Modified Local Adaptive Thresholding Techniques. In 2020 IEEE 16th International Conference on Automation Science and Engineering, CASE 2020. IEEE Computer Society. 2020. p. 1269-1274. 9216945. (IEEE International Conference on Automation Science and Engineering). doi: 10.1109/CASE48305.2020.9216945

A new QR Code Recognition Method using Deblurring and Modified Local Adaptive Thresholding Techniques

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