HEMTH: Small Depth Multilevel Thresholding for a Homomorphically Encrypted Image
HEMTH: Small Depth Multilevel Thresholding for a Homomorphically Encrypted Image
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DOI：
10.1109/mmsp55362.2022.9949585
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发表时间：
2022-09
期刊：
影响因子：
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通讯作者：
Paul Nam;Justin Shyi;Sunwoong Kim
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文献类型：
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作者：
Paul Nam;Justin Shyi;Sunwoong Kim
图像分割技术之一，多级阈值化，由于其低计算复杂性和高效的数据表示而广泛应用于许多计算机视觉应用中。当它用于网络物理系统和物联网时，需要特殊的技术来保护图像中的敏感信息。本文提出了一种新的基于同态加密（HE）的多级阈值方法。为了实现HE域中的比较运算，这不是基本的同态运算，采用数值方法。我们提出的方法并行执行比较操作以执行更多迭代并提高准确性。当数值比较操作的迭代次数为（5, 3）时，与传统的非基于 HE 的方法相比，所提出的三级阈值方法显示出平均峰值信噪比为 28 dB，并且在 PC 上需要 3 分钟。
One of the image segmentation techniques, multilevel thresholding, is widely used in many computer vision applications because of its low computational complexity and efficient data representation. When it is used in cyber-physical systems and internet-of-things, a special technique is required to protect the sensitive information in an image. This paper proposes a novel homomorphic encryption (HE)-based multilevel thresholding method. To implement a comparison operation in the HE domain, which is not a basic homomorphic operation, a numerical method is adopted. Our proposed method executes comparison operations in parallel to perform more iterations and increase accuracy. When the number of iterations in the numerical comparison operation is (5, 3), the proposed three-level thresholding method shows an average peak signal-to-noise ratio of 28 dB compared to a conventional non-HE-based method and takes 3 minutes on a PC.