The augmented reality (AR) system requires markers to recognize and locate virtual objects on the screens of mobile devices. However, both markers and objects must be registered via the online platform in advance. In addition, an AR marker can only pair with a fixed set of virtual objects, limiting the flexibility and immediacy of changing and updating these data. This paper incorporates the quick response barcode (QR code) into the AR system to address these issues. We propose an algorithm with two vital goals, including (1) generating differentiated virtual objects for different target users by using only one QR code as the marker and (2) concealing different private authentication in QR modules by applying the error correction capability. We then demonstrate the proposed approach via a simulation of two practical scenarios, the electronic catalogs for business applications, and differentiated instructional materials for digital learning. This paper contributes to AR and QR code research and practices.

In present times, barcode decoders on mobile phones can extract the data content of QR codes. However, this convenience raises concerns about security issues when using QR codes to transmit confidential information, such as e-tickets, coupons, and other private data. Moreover, current secret hiding techniques are unsuitable for QR code applications since QR codes are module-oriented, which is different from the pixel-oriented hiding manner. In this article, we propose an algorithm to conceal confidential information by changing the modules of the QR Code. This new scheme designs the triple module groups based on the concept of the error correction capability. Additionally, this manner can conceal two secret bits by changing only one module, and the amount of hidden confidential information can be twice the original amount. As a result, the ordinary data content (such as URL) can be extracted correctly from the generated QR code by any barcode decoders, which does not affect the readability of scanning. Furthermore, only authorized users with the secret key can further extract the concealed confidential information. This designed scheme can provide secure and reliable applications for the QR system.

An improved CLEAN algorithm for inverse synthetic aperture radar (ISAR) image processing is presented. An adaptive threshold is given to detect real targets after preprocessing by the CLEAN method. The cross-range resolution is emphasized. The results of processing are quite good.