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A Zero-Watermark Scheme Based on Quaternion Generalized Fourier Descriptor for Multiple Images

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摘要 Most of the existing zero-watermark schemes for medical images are only appropriate for a single grayscale image.When they protect a large number of medical images,repeating operations will cause a significant amount of time and storage costs.Hence,this paper proposes an efficient zero-watermark scheme for multiple color medical images based on quaternion generalized Fourier descriptor(QGFD).Firstly,QGFD is utilized to compute the feature invariants of each color image,then the representative features of each image are selected,stacked,and reshaped to generate a feature matrix,which is then binarized to get a binary feature image.Copyright information can be converted into the copyright image by using QR code technology,which contains more information.Finally,the zero-watermark image is constructed by executing the XOR operation on the copyright image and the feature image scrambled by the Cat map.In the experiment,different parameters are selected to determine the maximum number of images that the proposed scheme can protect simultaneously while achieving good robustness.The experimental results demonstrate that the proposed scheme can effectively resist common attacks,geometric attacks and joint attacks,and effectively improve the operation efficiency of the algorithm,thus effectively decreasing the time and storage cost of copyright protection for lots of medical images.
出处 《Computers, Materials & Continua》 SCIE EI 2022年第5期2633-2652,共20页 计算机、材料和连续体(英文)
基金 This work is supported by the National Natural Science Foundation of China[Grant Numbers 61972207,U1836208,U1836110,61672290] the Major Program of the National Social Science Fund of China[Grant Number 17ZDA092] by the National Key R&D Program of China[Grant Number 2018YFB1003205] by the Collaborative Innovation Center of Atmospheric Environment and Equipment Technology(CICAEET)fund,China by the Priority Academic Program Development of Jiangsu Higher Education Institutions(PAPD)fund.
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