Academic Research on QR Code

• Recognition of QR Code with mobile phones, Liu, Y., Yang, J., & Liu, M. (2008, July). InControl and Decision Conference, 2008. CCDC 2008. Chinese(pp. 203-206). IEEE. This paper suggests an innovative implementation of real-time Quick Response Code (QR Code) recognition that uses a mobile that is efficient in data transferring. The paper explains a mobile-based image processing system that can binarize, locate, segment as well as decode the QR code using experiments that suggest that these algorithms are vigorous to real-world scene image.
• QR code, Soon, T. J. (2008).Synthesis Journal,2008, 59-78. This article explains the QR code as a trademark for a form of matrix barcode which is a machine-readable optical label containing information on the item it is attached to. It then explains the various uses of the code which include consumer advertising, commercial tracking entertainment, and many others. 
• QR code security, Kieseberg, P., Leithner, M., Mulazzani, M., Munroe, L., Schrittwieser, S., Sinha, M., & Weippl, E. (2010, November). InProceedings of the 8th International Conference on Advances in Mobile Computing and Multimedia (pp. 430-435). ACM. This paper explains the various security risks that are by the QR codes. It gives an example of how attackers can encode malicious code onto the QR codes and then use them to replace the legitimate ones on advertisements in order to direct unknowing victims to phishing sites and other illegal sites. The paper also proposes design requirements in the code to facilitate further research into making it secure and usable. 
• Applying QR code in augmented reality applications, Kan, T. W., Teng, C. H., & Chou, W. S. (2009, December). InProceedings of the 8th International Conference on Virtual Reality Continuum and its Applications in Industry(pp. 253-257). ACM. This research discusses an augmented reality (AR) application that is based on the QR code and extracts information that is embedded in the code to present it in a 3D form. It combines the QR code with the traditional AR system to investigate what interesting and useful applications can be developed. The results if this investigation proves that this combination can be a success and this research some of the ways it can be used to bring convenience in the future.
• Utilizing QR code and mobile phones for blinds and visually impaired people, Al-Khalifa, H. S. (2008, July). InInternational Conference on Computers for Handicapped Persons(pp. 1065-1069). Springer, Berlin, Heidelberg. This article develops a system that utilizes QR codes on objects and scanned using a smartphone with the QR reader software to assist the visually impaired people to detect objects in their environment. It presents two scenarios that prove the usefulness of this system in real-time interactions with several distinct environments.
• A novel user authentication scheme based on QR-code, Liao, K. C., & Lee, W. H. (2010). Journal of networks,5(8), 937. This paper echoes the need for a simple and efficient authentication mechanism needed to secure the network system in the real environment. It explains the purpose of the password-based mechanism in preventing access by an unauthorized person. However, they are mostly impractical because they require costly specialized infrastructure, unlike the proposed QR code technique that is cost-effective and eliminates the usage of the password verification table. 
• The QR-code reorganization in illegible snapshots taken by mobile phones, Sun, A., Sun, Y., & Liu, C. (2007, August). InComputational Science and its Applications, 2007. ICCSA 2007. International Conference on(pp. 532-538). IEEE. This paper presents an algorithm for analyzing and fixing distortions in QR barcode images that is based on the code area finding through four corners detection for a 2D barcode. It details the process involved when using inverse perspective transformation to rebuild QR codes images that are distorted. It tests this algorithm using mobile phone images. 
• QR code and augmented reality-supported mobile English learning system, Liu, T. Y., Tan, T. H., & Chu, Y. L. (2010). InMobile multimedia processing(pp. 37-52). Springer, Berlin, Heidelberg. This study presents a QR code, and handheld augmented reality supported mobile learning system that defines the linked information between context-aware materials using the QR codes. This system also embeds a 3D animated virtual learning system in the learning device using AR technology. A case study is provided that shows the effectiveness of this system. 
• Fast QR codedetection in arbitrarily acquired images, Belussi, L., & Hirata, N. (2011, August). InGraphics, Patterns and Images (Sibgrapi), 2011 24th SIBGRAPI Conference on (pp. 281-288). IEEE. This article investigates a very effective method of focusing the detection process of QR codes in specific sections of the image that are promising and also a quick feature computation approach to classify the patterns. It also presents a post-processing algorithm that combines the results of the first section to determine whether the detected finder patterns are part of the QR code symbols. 
• Benchmarking the use of QR codein mobile promotion: Three studies in Japan, Okazaki, S., Li, H., & Hirose, M. (2012).Journal of Advertising Research,52(1), 102-117. This paper explores the various issues pertaining to QR codes such as its actual use in different media, motivations for consumers to utilize it and the risks resulting from using QR codes. It uses three studies conducted in Japan to indicate that QR codes mostly used in print media to promote loyalty programs and that perceived risks vary depending on the context that consumer scan QR codes. 
• A General Scheme for Extracting QR Codefrom a non-uniform background in Camera Phones and Applications, Chang, Y. H., Chu, C. H., & Chen, M. S. (2007, December). InMultimedia, 2007. ISM 2007. Ninth IEEE International Symposium on(pp. 123-130). IEEE. This article explains the applications of the QR code and suggests a practical algorithm that is used to extract QR code from the non-uniform background. It differs from previous studies since it has a more accurate approach for the recognition of QR code and a more realistic use in a mobile information environment.