A Privacy-Preserving Image Retrieval Scheme Using A Codebook Generated From Independent Plain-Image Dataset

TL;DR

This paper introduces a privacy-preserving image retrieval method that uses a codebook generated from an independent dataset, ensuring high accuracy without recalculating the codebook for each user.

Contribution

The novel approach generates a codebook from an independent dataset, enabling consistent high retrieval accuracy without recalculating for each image set.

Findings

Maintains high retrieval accuracy with independent dataset-based codebook

Eliminates need for codebook recalculation for new images

Demonstrates effectiveness on encrypted images

Abstract

In this paper, we propose a privacy-preserving image-retrieval scheme using a codebook generated by using a plain-image dataset. Encryption-then-compression (EtC) images, which were proposed for EtC systems, have been used in conventional privacy-preserving image-retrieval schemes, in which a codebook is generated from EtC images uploaded by image owners, and extended SIMPLE descriptors are then calculated as image descriptors by using the codebook. In contrast, in the proposed scheme, a codebook is generated from a dataset independent of uploaded images. The use of an independent dataset enables us not only to use a codebook that does not require recalculation but also to constantly provide a high retrieval accuracy. In an experiment, the proposed scheme is demonstrated to maintain a high retrieval performance, even if codebooks are generated from a plain image dataset independent of image owners' encrypted images.