Privacy-Preserving Image Retrieval Based on Thumbnail-Preserving Visual Features

Images are generally uploaded to the cloud in plaintext and can be retrieved in the cloud, but privacy may be exposed. To solve this problem, Privacy Preserving Content Based Image Retrieval (PPCBIR) system was proposed. In this system, noise-like image encryption algorithm was used in the early scheme, and Thumbnail Preserving Encryption (TPE) technology was proposed later to balance image privacy and visual usability. However, the existing TPE schemes supporting retrieval have shortcomings in mining the visual usability of TPE images, which limits the retrieval accuracy. Based on this, we propose a VF-PPCBIR scheme combining TPE and image visual features to improve retrieval efficiency and accuracy while ensuring image privacy. Specifically, we redesign a new TPE algorithm for lossless encryption and decryption of arbitrary size images. The design concept of the encryption algorithm is novel, and the encryption effect is more stable. The retrieval process generates thumbnails of the retrieved image and extracts local features in the spatial domain, which are matched with the features extracted from TPE thumbnails in the cloud, and the user can directly select the desired image. In addition, the retrieval scheme uses adjustable feature algorithm to achieve approximate similarity between the ciphertext and the plaintext thumbnail, to achieve accurate feature matching. The experimental results show that the time cost, and mean average precision (mAP) can reach 9.121s and 64.343%, respectively.