Work

Information Hiding in QR Code Images via Module Content Modification Based on Corner-Pixel Grayscale Adjustment

Year: 2026

Type: article

Abstract: QR codes are widely used in digital authentication, mobile payment, access control, and information exchange, making QR code-based covert communication and hidden message delivery relevant to cybersecurity applications. This study proposes a QR code-based information-hiding method via module content modification based on corner-pixel grayscale adjustment. Secret bits are embedded into a QR code image through subtle grayscale adjustments of module corner pixels. To reduce visually noticeable embedding artifacts, embedding in adjacent module corners that share identical original grayscale values is prohibited, thereby preventing noticeable local contrast that could reveal hidden content. Gradient-based smoothing is further applied to suppress contrast artifacts within module interiors after embedding. A theoretical analysis of bilinear interpolation and quarter subregion averages is presented to justify the proposed extraction thresholds. Experiments across multiple QR code versions, error-correction levels, and embedding parameters show that the proposed method achieves an average embedding rate of approximately 1.9 bits per module while generally maintaining QR code readability across the tested commercial scanning devices. Exploratory random-noise experiments further show that hidden-message recovery remains possible up to the observed highest tolerable noise rates in the tested realizations. A comparison with four representative methods indicates that the proposed method achieves substantially higher embedding rates under the adopted comparison framework, demonstrating its potential for high-capacity QR code information-hiding while enabling successful hidden-message recovery under the evaluated conditions.

Source: Applied Sciences

DOI: 10.3390/app16178498

Authors: Da-Chun Wu, Yuan-Ming Wu

Institution: National Kaohsiung University of Science and Technology

Language: English

Topic: Advanced Steganography and Watermarking Techniques

Subfield: Computer Vision and Pattern Recognition

Field: Computer Science

Domain: Physical Sciences

Open Access status: gold

Estimated APC paid: $2,896

Funder: National Science and Technology Council