Abstract
QR codes are widely used in the traceability of commodities, but the QR codes are easy to become blurred during the acquisition process of mobile phones, which affects their normal identification, so it is necessary to deblur them. This paper proposes a sub-regional deblurring method based on prior knowledge of the gradient and intensity of positioning patterns. Firstly, the QR code is divided into four regions according to the positions of three finder positioning patterns and one alignment positioning pattern. The content invariance of the four positioning patterns can avoid the interference of the content to the estimation of the blur kernel, and also take into account the non-uniformity of the QR code blur. Then the gradient and intensity priors are used to estimate the blur kernels of the position patterns in the four regions, and the calculated blur kernels are applied to the corresponding respective regions for deblurring. Finally, the four deblurred regions are stitched together to obtain the entire deblurring image. The experimental results show that the proposed method performs well in terms of deblurring effect and computational time, surpassing similar deblurring methods.
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Acknowledgements
This research is supported by the National Key Research and Development Program of China (Grant No.2020YFF0304902) and the Science and Technology Research Project of Jiangxi Provincial Department of Education (Grant No.GJJ202511).
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Zheng, H., Guo, Z., Liu, C. et al. Blind deblurring of QR code using intensity and gradient prior of positioning patterns. Vis Comput 40, 441–455 (2024). https://doi.org/10.1007/s00371-023-02792-3
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DOI: https://doi.org/10.1007/s00371-023-02792-3