ART-UP: A Novel Method for Generating Scanning-robust Aesthetic QR codes

TL;DR

This paper introduces a new method for generating aesthetic QR codes that are both visually appealing and robust to scanning in various environments, using a module-based probability model and hierarchical adjustment.

Contribution

The paper presents a novel hierarchical approach that balances visual quality and scanning robustness in aesthetic QR code generation, outperforming existing algorithms.

Findings

High decoding success rate in diverse environments

Enhanced visual quality of aesthetic QR codes

Effective balance between aesthetics and robustness

Abstract

QR codes are usually scanned in different environments, so they must be robust to variations in illumination, scale, coverage, and camera angles. Aesthetic QR codes improve the visual quality, but subtle changes in their appearance may cause scanning failure. In this paper, a new method to generate scanning-robust aesthetic QR codes is proposed, which is based on a module-based scanning probability estimation model that can effectively balance the tradeoff between visual quality and scanning robustness. Our method locally adjusts the luminance of each module by estimating the probability of successful sampling. The approach adopts the hierarchical, coarse-to-fine strategy to enhance the visual quality of aesthetic QR codes, which sequentially generate the following three codes: a binary aesthetic QR code, a grayscale aesthetic QR code, and the final color aesthetic QR code. Our approach also can be used to create QR codes with different visual styles by adjusting some initialization parameters. User surveys and decoding experiments were adopted for evaluating our method compared with state-of-the-art algorithms, which indicates that the proposed approach has excellent performance in terms of both visual quality and scanning robustness.