Secure content‐based image retrieval using modified Euclidean distance for encrypted features,Transactions on Emerging Telecommunications Technologies

当前位置： X-MOL 学术 › Trans. Emerg. Telecommun. Technol. › 论文详情

Our official English website, www.x-mol.net, welcomes your feedback! (Note: you will need to create a separate account there.)

Secure content‐based image retrieval using modified Euclidean distance for encrypted features
Transactions on Emerging Telecommunications Technologies ( IF 2.5 ) Pub Date : 2020-07-13 , DOI: 10.1002/ett.4013
Mukul Majhi ₁ , Arup Kumar Pal ₁ , SK Hafizul Islam ₂ , Muhammad Khurram Khan ₃

Affiliation

In this article, a secure image retrieval scheme is proposed, which focuses on providing satisfactory retrieval results, and the framework searches relevant images even in an encrypted domain without compromising the performance of the retrieval process. Initially, bit‐level features have been endeavored from the luminance component of the image, from which statistical parameters are computed to generate more intrinsic values. These values are subsequently divided into bins to configure two histograms, which effectively reduce the length of the feature vector. These histograms are then eventually combined with quantized chrominance features to enhance the discriminative property of the feature vector. Since the proposed scheme is in the encrypted domain, conventional similarity measure distance for the image is not well suited. So, a modified Euclidean distance is incorporated, which is modeled to work with encrypted features. To comprehend the security, a piecewise logistic map sequence is considered, where seed values are assimilated to generate two secret keys. As a result, not only the system provides an efficient, secure retrieval system but also cryptographic components have no impact on its retrieval efficiency, and satisfactory results are obtained. Experimental results on Corel‐1K and GHIM‐10K illustrate decent performance in retrieval as compared to existing work in the retrieval domain.

中文翻译：

使用修改后的欧氏距离对加密特征进行安全的基于内容的图像检索

在本文中，提出了一种安全的图像检索方案，该方案着重于提供令人满意的检索结果，并且该框架即使在加密域中也可以搜索相关图像，而不会影响检索过程的性能。最初，人们已经从图像的亮度分量中尝试了比特级特征，并从中计算出统计参数以生成更多的固有值。随后将这些值划分为bin，以配置两个直方图，从而有效地减少了特征向量的长度。然后，将这些直方图最终与量化的色度特征组合在一起，以增强特征向量的判别特性。由于所提出的方案位于加密域中，因此图像的常规相似性度量距离不太适合。所以，合并了修改后的欧几里得距离，该距离被建模为与加密特征一起使用。为了理解安全性，考虑了分段逻辑映射序列，其中种子值被同化以生成两个秘密密钥。结果，不仅该系统提供了有效，安全的检索系统，而且密码组件对其检索效率没有影响，并且获得了令人满意的结果。与检索领域中的现有工作相比，Corel-1K和GHIM-10K上的实验结果说明了检索方面的出色表现。安全的检索系统，但密码组件对其检索效率没有影响，并且获得了令人满意的结果。与检索领域中的现有工作相比，Corel-1K和GHIM-10K上的实验结果说明了检索方面的出色表现。安全的检索系统，但密码组件对其检索效率没有影响，并且获得了令人满意的结果。与检索领域中的现有工作相比，Corel-1K和GHIM-10K上的实验结果说明了检索方面的出色表现。

更新日期：2020-07-13

点击分享查看原文

点击收藏

阅读更多本刊最新论文本刊介绍/投稿指南11