Abstract
To evaluate the visual quality in visual secret sharing schemes, most of the existing metrics fail to generate fair and uniform quality scores for tested reconstructed images. We propose a new approach to measure the visual quality of the reconstructed image for visual secret sharing schemes. We developed an object detection method in the context of secret sharing, detecting outstanding local features and global object contour. The quality metric is constructed based on the object detection-weight map. The effectiveness of the proposed quality metric is demonstrated by a series of experiments. The experimental results show that our quality metric based on secret object detection outperforms existing metrics. Furthermore, it is straightforward to implement and can be applied to various applications such as performing the security test of the visual secret sharing process.
Highlights
IntroductionNamed visual cryptography, encrypts the secret image by generating random-looking shares
Visual secret sharing, named visual cryptography, encrypts the secret image by generating random-looking shares
We proposed a novel metric to measure the visual quality of the reconstructed image for visual secret sharing
Summary
Named visual cryptography, encrypts the secret image by generating random-looking shares. The quality of the reconstructed image is one of the most important issues of visual secret sharing. Other scholars [7, 8] have used some well-known image quality metrics such as peak signal-to-noise ratio (PSNR) and mean squared error (MSE) to test the difference between the reconstruction image and secret image. We proposed a novel metric to measure the visual quality of the reconstructed image for visual secret sharing.
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