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Privacy-Preserving Content-Based Image Retrieval Using Compressible Encrypted Images

Kenta Iida, Hitoshi Kiya

2020IEEE Access37 citationsDOIOpen Access PDF

Abstract

In this article, we propose a novel content-based image-retrieval (CBIR) scheme using compressible encrypted images called “encryption-then-compression (EtC) images.” The proposed scheme allows us not only to directly retrieve images from visually protected images but to also apply EtC images that can be compressed by using the JPEG standard for the first time. In addition, the sensitive management of secret keys is not required in our framework. The proposed retrieval scheme is carried out on the basis of weighted searching images with MPEG-7-powered localized descriptors (weighted SIMPLE descriptors) combining scalable color descriptor (SCD) or color and edge directivity descriptor (CEDD). Weighted SIMPLE descriptors are extended, and CEDD is also modified to avoid the influence of image encryption. In an experiment, the proposed scheme is demonstrated to have almost no degradation in retrieval performance compared with conventional content-based retrieval methods with plain images under the use of two datasets. In addition, the proposed scheme is shown to outperform conventional privacy-preserving CBIR schemes including state-of-the-art ones in terms of mean average precision (mAP) scores.

Topics & Concepts

Computer scienceEncryptionContent-based image retrievalImage retrievalArtificial intelligenceComputer visionScheme (mathematics)Pattern recognition (psychology)JPEGImage (mathematics)MathematicsMathematical analysisOperating systemAdvanced Image and Video Retrieval TechniquesImage Retrieval and Classification TechniquesAdvanced Steganography and Watermarking Techniques
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