{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,18]],"date-time":"2026-06-18T10:36:41Z","timestamp":1781779001991,"version":"3.54.5"},"reference-count":30,"publisher":"Springer Science and Business Media LLC","issue":"1","license":[{"start":{"date-parts":[[2023,3,4]],"date-time":"2023-03-04T00:00:00Z","timestamp":1677888000000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2023,3,4]],"date-time":"2023-03-04T00:00:00Z","timestamp":1677888000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"}],"funder":[{"name":"the Science and Technology Research Project of Jiangxi Provincial Department of Education","award":["GJJ202511"],"award-info":[{"award-number":["GJJ202511"]}]},{"name":"National Key Research and Development Program of China","award":["2020YFF0304902"],"award-info":[{"award-number":["2020YFF0304902"]}]}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Vis Comput"],"published-print":{"date-parts":[[2024,1]]},"DOI":"10.1007\/s00371-023-02792-3","type":"journal-article","created":{"date-parts":[[2023,3,4]],"date-time":"2023-03-04T14:02:40Z","timestamp":1677938560000},"page":"441-455","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":8,"title":["Blind deblurring of QR code using intensity and gradient prior of positioning patterns"],"prefix":"10.1007","volume":"40","author":[{"given":"Hong","family":"Zheng","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5445-1400","authenticated-orcid":false,"given":"Zhongyuan","family":"Guo","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Chang","family":"Liu","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Xi","family":"Li","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Tianyu","family":"Wang","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Changhui","family":"You","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","published-online":{"date-parts":[[2023,3,4]]},"reference":[{"issue":"3","key":"2792_CR1","first-page":"277","volume":"45","author":"CH Lee","year":"2019","unstructured":"Lee, C.H., Bae, J.T., Hong, J.T.: Establishment of cosmetic raw material weighing and bulk manufacturing management system using bar code, QR code and database. J. Soc. Cosmet. Sci. Korea 45(3), 277\u2013285 (2019)","journal-title":"J. Soc. Cosmet. Sci. Korea"},{"key":"2792_CR2","unstructured":"Vijayalakshmi, S.: A Project report on big data integration for tracking the cosmetic inventory and Qc Testing. Diss. CMR Institute of Technology. Bangalore, 2020"},{"issue":"6","key":"2792_CR3","doi-asserted-by":"publisher","first-page":"3486","DOI":"10.3390\/su13063486","volume":"13","author":"S Dey","year":"2021","unstructured":"Dey, S., Saha, S., Singh, A.K., et al.: FoodSQRBlock: digitizing food production and the supply chain with blockchain and QR code in the cloud. Sustainability 13(6), 3486 (2021)","journal-title":"Sustainability"},{"key":"2792_CR4","doi-asserted-by":"publisher","DOI":"10.1016\/j.fpsl.2021.100638","volume":"28","author":"J Qian","year":"2021","unstructured":"Qian, J., Xing, B., Zhang, B., et al.: Optimizing QR code readability for curved agro-food packages using response surface methodology to improve mobile phone-based traceability. Food Packag. Shelf Life 28, 100638 (2021)","journal-title":"Food Packag. Shelf Life"},{"key":"2792_CR5","doi-asserted-by":"crossref","unstructured":"Mishra, N., Mistry. S., Choudhary. S., et al.: Food traceability system using blockchain and QR Code[M]\/\/IC-BCT 2019. pp. 33\u201343. Springer, Singapore (2020)","DOI":"10.1007\/978-981-15-4542-9_4"},{"key":"2792_CR6","volume":"48","author":"R Focardi","year":"2019","unstructured":"Focardi, R., Luccio, F.L., Wahsheh, H.A.M.: Usable security for QR code. J. Inf. Secur. Appl. 48, 102369 (2019)","journal-title":"J. Inf. Secur. Appl."},{"key":"2792_CR7","doi-asserted-by":"crossref","unstructured":"\u0160andi, S., Radonji\u0107, S., Drobnjak, J., et al.: Smart tags for brand protection and anti-counterfeiting in wine industry[C]\/\/2018 23rd International Scientific-Professional Conference on Information Technology (IT). pp. 1\u20135. IEEE (2018)","DOI":"10.1109\/SPIT.2018.8350849"},{"key":"2792_CR8","doi-asserted-by":"publisher","DOI":"10.1016\/j.iot.2021.100375","volume":"14","author":"T Popovi\u0107","year":"2021","unstructured":"Popovi\u0107, T., Kr\u010do, S., Mara\u0161, V., et al.: A novel solution for counterfeit prevention in the wine industry based on IoT, smart tags, and crowd-sourced information. Internet Things 14, 100375 (2021)","journal-title":"Internet Things"},{"issue":"8","key":"2792_CR9","doi-asserted-by":"publisher","first-page":"6789","DOI":"10.1109\/JIOT.2020.3035697","volume":"8","author":"Y Yan","year":"2020","unstructured":"Yan, Y., Zou, Z., Xie, H., et al.: An IoT-based anti-counterfeiting system using visual features on QR code. IEEE Internet Things J. 8(8), 6789\u20136799 (2020)","journal-title":"IEEE Internet Things J."},{"issue":"6","key":"2792_CR10","doi-asserted-by":"publisher","first-page":"923","DOI":"10.1049\/iet-ipr.2018.5792","volume":"13","author":"XY Yu","year":"2019","unstructured":"Yu, X.Y., Xie, W.: Real-time recovery and recognition of motion blurry QR code image based on fractional order deblurring method. IET Image Proc. 13(6), 923\u2013930 (2019)","journal-title":"IET Image Proc."},{"key":"2792_CR11","doi-asserted-by":"publisher","first-page":"117","DOI":"10.1016\/j.patrec.2018.04.036","volume":"111","author":"N Liu","year":"2018","unstructured":"Liu, N., Du, Y., Xu, Y.: QR codes blind deconvolution algorithm based on binary characteristic and L0 norm minimization. Pattern Recogn. Lett. 111, 117\u2013123 (2018)","journal-title":"Pattern Recogn. Lett."},{"key":"2792_CR12","doi-asserted-by":"crossref","unstructured":"Li, J., Hu, B., Cao, Z.: A new QR code recognition method using deblurring and modified local adaptive thresholding techniques[C]\/\/2020 IEEE 16th International Conference on Automation Science and Engineering (CASE). pp. 1269\u20131274. IEEE (2020)","DOI":"10.1109\/CASE48305.2020.9216945"},{"key":"2792_CR13","doi-asserted-by":"publisher","DOI":"10.1016\/j.ijleo.2020.164902","volume":"219","author":"Y Shi","year":"2020","unstructured":"Shi, Y., He, B., Zhu, M., et al.: Fast linear motion deblurring for 2D barcode. Optik 219, 164902 (2020)","journal-title":"Optik"},{"issue":"12","key":"2792_CR14","doi-asserted-by":"publisher","first-page":"5306","DOI":"10.1109\/TIP.2013.2284873","volume":"22","author":"F Conte","year":"2013","unstructured":"Conte, F., Germani, A., Iannello, G.: A kalman filter approach for denoising and deblurring 3-d microscopy images. IEEE Trans. Image Process. 22(12), 5306\u20135321 (2013)","journal-title":"IEEE Trans. Image Process."},{"issue":"9","key":"2792_CR15","first-page":"12","volume":"4","author":"M Kaur","year":"2014","unstructured":"Kaur, M., Bhandari, A.S., Singh, C.: Deblurring, localization and geometry correction of 2D QR bar codes using Richardson Lucy method. Int. J. Eng. Res. Appl. 4(9), 12\u201317 (2014)","journal-title":"Int. J. Eng. Res. Appl."},{"key":"2792_CR16","unstructured":"Wu, Y.: Deblurring barcodes images based on L0-regularization (D). Zhejiang University (2018)"},{"key":"2792_CR17","unstructured":"Tu, D., Gan, Y., Xu, Z.: A Real-time deblurring algorithm for the QR barcode images. Comput. Eng. Sci. 3 (2007)"},{"key":"2792_CR18","first-page":"117","volume":"2015","author":"G S\u00f6r\u00f6s","year":"2015","unstructured":"S\u00f6r\u00f6s, G., Semmler, S., Humair, L., et al.: Fast blur removal for wearable QR code scanners[C]\/\/Proceedings of the. ACM Int. Symp. Wearable Comput. 2015, 117\u2013124 (2015)","journal-title":"ACM Int. Symp. Wearable Comput."},{"issue":"9","key":"2792_CR19","doi-asserted-by":"publisher","first-page":"2864","DOI":"10.1109\/TIP.2015.2432675","volume":"24","author":"Y Van Gennip","year":"2015","unstructured":"Van Gennip, Y., Athavale, P., Gilles, J., et al.: A regularization approach to blind deblurring and denoising of QR barcodes. IEEE Trans. Image Process. 24(9), 2864\u20132873 (2015)","journal-title":"IEEE Trans. Image Process."},{"key":"2792_CR20","unstructured":"Rioux, G., Scarvelis, C., Choksi, R., et al.: Blind deblurring of barcodes via Kullback-Leibler divergence. IEEE transactions on pattern analysis and machine intelligence, 2019"},{"key":"2792_CR21","doi-asserted-by":"crossref","unstructured":"Wang, M., Chen, K., Lin, F.: Multi-residual generative adversarial networks for QR code deblurring[C]\/\/International Conference on Electronic Information Technology (EIT 2022). SPIE, 12254, 589\u2013594 (2022)","DOI":"10.1117\/12.2640025"},{"key":"2792_CR22","doi-asserted-by":"publisher","first-page":"351","DOI":"10.1016\/j.neucom.2022.04.041","volume":"493","author":"J Li","year":"2022","unstructured":"Li, J., Zhang, D., Zhou, M.C., et al.: A motion blur QR code identification algorithm based on feature extracting and improved adaptive thresholding[J]. Neurocomputing 493, 351\u2013361 (2022)","journal-title":"Neurocomputing"},{"key":"2792_CR23","doi-asserted-by":"crossref","unstructured":"Tiwari S.: An introduction to QR code technology[C]\/\/2016 international conference on information technology (ICIT). pp. 39\u201344. IEEE (2016)","DOI":"10.1109\/ICIT.2016.021"},{"issue":"2","key":"2792_CR24","doi-asserted-by":"publisher","first-page":"342","DOI":"10.1109\/TPAMI.2016.2551244","volume":"39","author":"J Pan","year":"2016","unstructured":"Pan, J., Hu, Z., Su, Z., et al.: L0-regularized intensity and gradient prior for deblurring text images and beyond. IEEE Trans. Pattern Anal. Mach. Intell. 39(2), 342\u2013355 (2016)","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"key":"2792_CR25","doi-asserted-by":"crossref","unstructured":"Yan, Y., Ren, W., Guo, Y., Wang, R., Cao, X.: Image deblurring via extreme channels prior. In Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pp. 4003\u20134011 (2017)","DOI":"10.1109\/CVPR.2017.738"},{"key":"2792_CR26","doi-asserted-by":"crossref","unstructured":"Wen, F., Ying, R., Liu, Y., et al.: A simple local minimal intensity prior and an improved algorithm for blind image deblurring. IEEE Transactions on Circuits and Systems for Video Technology (2020)","DOI":"10.1109\/TCSVT.2020.3034137"},{"issue":"10","key":"2792_CR27","doi-asserted-by":"publisher","first-page":"2447","DOI":"10.1109\/TMM.2019.2907475","volume":"21","author":"Y Huang","year":"2019","unstructured":"Huang, Y., Niu, B., Guan, H., et al.: Enhancing image watermarking with adaptive embedding parameter and PSNR guarantee. IEEE Trans. Multimed. 21(10), 2447\u20132460 (2019)","journal-title":"IEEE Trans. Multimed."},{"issue":"3","key":"2792_CR28","doi-asserted-by":"publisher","first-page":"8","DOI":"10.4236\/jcc.2019.73002","volume":"7","author":"U Sara","year":"2019","unstructured":"Sara, U., Akter, M., Uddin, M.S.: Image quality assessment through FSIM, SSIM, MSE and PSNR\u2014a comparative study. J. Comput. Commun. 7(3), 8\u201318 (2019)","journal-title":"J. Comput. Commun."},{"issue":"6","key":"2792_CR29","doi-asserted-by":"publisher","first-page":"8423","DOI":"10.1007\/s11042-020-10035-z","volume":"80","author":"DRIM Setiadi","year":"2021","unstructured":"Setiadi, D.R.I.M.: PSNR vs SSIM: imperceptibility quality assessment for image steganography. Multimed. Tools Appl. 80(6), 8423\u20138444 (2021)","journal-title":"Multimed. Tools Appl."},{"issue":"2","key":"2792_CR30","doi-asserted-by":"publisher","first-page":"384","DOI":"10.1049\/iet-ipr.2019.0750","volume":"14","author":"X Yang","year":"2020","unstructured":"Yang, X., Wang, T., Ji, G.: No-reference image quality assessment via structural information fluctuation. IET Image Process 14(2), 384\u2013396 (2020)","journal-title":"IET Image Process"}],"container-title":["The Visual Computer"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s00371-023-02792-3.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s00371-023-02792-3\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s00371-023-02792-3.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,1,21]],"date-time":"2024-01-21T13:05:32Z","timestamp":1705842332000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s00371-023-02792-3"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2023,3,4]]},"references-count":30,"journal-issue":{"issue":"1","published-print":{"date-parts":[[2024,1]]}},"alternative-id":["2792"],"URL":"https:\/\/doi.org\/10.1007\/s00371-023-02792-3","relation":{},"ISSN":["0178-2789","1432-2315"],"issn-type":[{"value":"0178-2789","type":"print"},{"value":"1432-2315","type":"electronic"}],"subject":[],"published":{"date-parts":[[2023,3,4]]},"assertion":[{"value":"23 January 2023","order":1,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"4 March 2023","order":2,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}},{"order":1,"name":"Ethics","group":{"name":"EthicsHeading","label":"Declarations"}},{"value":"The authors declare no conflict of interest.","order":2,"name":"Ethics","group":{"name":"EthicsHeading","label":"Conflict of interest"}}]}}