Acta Photonica Sinica, Volume. 50, Issue 7, 91(2021)

Fast Blind Restoration of QR Code Images Based on Blurred Imaging Mechanism

Rongjun CHEN1,2, Zhijun ZHENG1, Huimin ZHAO1, Jinchang REN1,3、*, and Hongzhou TAN2
Author Affiliations
  • 1School of Computer Science, Guangdong Polytechnic Normal University, Guangzhou50665, China
  • 2School of Electronics and Information Technology, Sun Yat-sen University, Guangzhou510006, China
  • 3National Subsea Centre, Robert Gordon University, Aberdeen, AB10 7RQ, U.K.
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    A fast blind restoration method of QR code images was proposed based on a blurred imaging mechanism. On the basis of the research on the centroid invariance of the blurred imaging diffuse light spots, the circular finder pattern is designed. When the image is blurred, the centroid of the pattern and the position of the QR code symbol can be quickly detected by methods such as connected components. Moreover, combined with step edge characteristics, gradient and intensity characteristics, edge detection technology, and optical imaging mechanism, the defocus radius of the blurred QR code image can be quickly and accurately estimated. Furthermore, the Wiener filter is applied to restore the QR code image quickly and effectively. Compared with the other algorithms, the proposed method has improved deblurring results in both structural similarity and peak signal-to-noise ratio, especially in the recovery speed. The average recovery time is 0.329 2 s. Experimental results show that this method can estimate the defocus radius with high accuracy and can quickly realize the blind restoration of QR code images. It has the advantages of rapidity and robustness, which are convenient for embedded hardware implementation and suitable for barcode identification-related industrial Internet of Things application scenarios.

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    Rongjun CHEN, Zhijun ZHENG, Huimin ZHAO, Jinchang REN, Hongzhou TAN. Fast Blind Restoration of QR Code Images Based on Blurred Imaging Mechanism[J]. Acta Photonica Sinica, 2021, 50(7): 91

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    Paper Information

    Category: Image Processing

    Received: May. 16, 2021

    Accepted: Jul. 8, 2021

    Published Online: Sep. 1, 2021

    The Author Email: REN Jinchang (jinchang.ren@ieee.org)

    DOI:10.3788/gzxb20215007.0710003

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