Color brings extra data capacity for QR codes, but it also brings tremendous challenges to the decoding because of color interference and illumination variation, especially for high-density QR codes. In this paper, we put forth a framework for high-capacity QR codes, HiQ, which optimizes the decoding algorithm for high-density QR codes to achieve robust and fast decoding on mobile devices, and adopts a learning-based approach for color recovery. Moreover, we propose a robust geometric transformation algorithm to correct the geometric distortion. We also provide a challenging color QR code dataset, CUHK-CQRC, which consists of 5390 high-density color QR code samples captured by different smartphones under different lighting conditions. Experimental results show that HiQ outperforms the baseline [1] by 286% in decoding success rate and 60% in bit error rate.

All printed documents/credentials are potentially subject to counterfeiting and forgery. Conventional counterfeiting solutions such as watermarking or printing using special-quality paper are not cost-effective. Certification via authorized chops/stamps is low-cost but only provides a false sense of security/ authenticity. To tackle this problem, we propose AuthPaper: a cost-effective, secure solution for authenticating paper-based documents/credentials using off-the-shelf handheld devices such as smartphones and tablets. The key idea is to extend existing 2D barcodes, e.g. the QR code, to carry a large amount of self-describing, and most importantly, authenticated data of all types containing text, image and other binary ones. By embedding the Authenticated 2D barcode as an integral part of a paper-based document, the authenticity of the document can be readily verified by comparing its content with the corresponding digitally-signed content contained in the Authenticated 2D barcode. No online network-access or real-time communication with the document issuer is required during the document verification process. We have built a prototype using Android smartphones to prove that the proposed system is feasible. As shown by measurements, our prototype can accurately create and decode 2D barcodes carrying different sets of document data including images while the increases in processing time and memory usage are negligible.

All printed documents and credentials are potentially subject to counterfeiting and forgery. Conventional counterfeiting solutions such as watermarking or printing with special-quality paper are not cost-effective. Certification via authorized chops/ stamps is low-cost but only provides a false sense of security/ authenticity. While embedding a serial number in the document for online verification is low-cost and secure, it is not applicable without Internet connection. We demonstrate AuthPaper (Authenticated Paper) to solve these problems by: 1) Digitally sign on the document to be protected; 2) Put the original content, digital signature and optionally the signer's certificate in a self-describing encapsulation; 3) Generate a 2D barcode (e.g. QR code) to carry the encapsulation and embed it as an integral part of the paper document. Note that the information carried in Authenticated QR Code is 40 to 50 times more than a typical one (≈50 Bytes). The biggest technical challenge is to scan and decode such densely packed codes in a robust manner. We have developed an Android application to address the challenge. In short, AuthPaper provides a secure, low-cost and offline method for document authentication.