Image-Like 2D Barcodes Using Generalizations of the Kuznetsov–Tsybakov Problem

In this paper, we propose a novel method for generating visually appealing two-dimensional (2D) barcodes that resemble meaningful images to human observers. The technology of 2D barcodes, currently dominated by quick response codes, is widely adopted in many applications, including product tracking, document management, and general marketing. Such barcodes typically lack user friendly appearance and do not convey any visual significance to human observers. The proposed method addresses this problem by allowing 2D barcodes to resemble an arbitrary image or a logo. Our method is based on a generalization of the Kuznetsov–Tsybakov problem that served as a foundation for wet paper codes, commonly adopted in digital steganography. We introduce weaker statistical constraints to obtain additional flexibility allowing the barcode to assume the appearance of an arbitrary pattern. This paper provides the theoretical analysis of the proposed coding framework and a practical algorithm for rapid approximation of the optimal code. We also discuss the introduction of error correction capabilities, and experimentally evaluate a prototype implementation in a smartphone-based acquisition scenario.