A Genetic Algorithm-Based Reversible Data Hiding Approach for Enhancing QR Code Security
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Abstract
The problems concerning efficient RDH algorithms are often complex and involve a combination of several methods. Embedding capacity and each image require different optimum parameters. This paper presents an investigation of the parameters for the reversible data hiding algorithm for QR code images. One tool was used for finding those optimal parameters. The genetic algorithm was applied to find the weighting value and level of Expanded Variance Mean sorting that provides the lowest possible distortion for each image and each embedding capacity. Using pixel sorting before embedding is essential for modern RDH algorithms to reduce the location map size, thus allowing more information to be embedded with less distortion. The path of the threshold values of the QR code image (close to 0 and 255) was also checked to ensure the best embedding interval. The performance test for the proposed method used six QR code images (Image with the smallest and least variance to image with the largest and most variance), and the hidden bits were random. The experimental results of the proposed method show that the peak signal-to-noise ratio values are superior compared to the previous two works, averaging about 2 dB compared to LV+EMSW and 0.5 dB compared to EVM+EMSW. In the future, it should be possible to explore multi-bit embedding schemes for smooth areas that enable more embedding and still have low distortion.
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