A regularization approach to blind deblurring and denoising of QR barcodes

van Gennip, Yves; Athavale, Prashant; Gilles, J�r�me; Choksi, Rustum

Abstract

QR bar codes are prototypical images for which part of the image is a priori known (required patterns). Open source bar code readers, such as ZBar, are readily available. We exploit both these facts to provide and assess purely regularization-based methods for blind deblurring of QR bar codes in the presence of noise.

Citation

van Gennip, Y., Athavale, P., Gilles, J., & Choksi, R. (2015). A regularization approach to blind deblurring and denoising of QR barcodes. IEEE Transactions on Image Processing, 24(9), https://doi.org/10.1109/TIP.2015.2432675

• Journal Article Type: Article
• Publication Date: Sep 1, 2015
• Deposit Date: Nov 12, 2015
• Publicly Available Date: Nov 12, 2015
• Journal: IEEE Transactions on Image Processing
• Print ISSN: 1057-7149
• Electronic ISSN: 1941-0042
• Publisher: Institute of Electrical and Electronics Engineers
• Peer Reviewed: Peer Reviewed
• Volume: 24
• Issue: 9
• DOI: https://doi.org/10.1109/TIP.2015.2432675
• Keywords: QR bar code, blind deblurring, finder pattern, TV regularization, TV flow
• Public URL: https://nottingham-repository.worktribe.com/output/982617
• Publisher URL: http://ieeexplore.ieee.org/xpl/articleDetails.jsp?arnumber=7106501
• Additional Information: (c) 2015 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other users, including reprinting/ republishing this material for advertising or promotional purposes, creating new collective works for resale or redistribution to servers or lists, or reuse of any copyrighted components of this work in other works.