Open Access
ARTICLE
QDCT Encoding-Based Retrieval for Encrypted JPEG Images
Qiuju Ji1, Peipeng Yu1, Zhihua Xia1, *
1 School of Computer and Software, Nanjing University of Information Science and Technology, Nanjing,
210044, China.
* Corresponding Author: Zhihua Xia. Email: .
Journal on Big Data 2020, 2(1), 33-51. https://doi.org/10.32604/jbd.2020.01004
Received 05 January 2020; Accepted 13 May 2020; Issue published 07 September 2020
Abstract
Aprivacy-preserving search model for JPEG images is proposed in paper, which
uses the bag-of-encrypted-words based on QDCT (Quaternion Discrete Cosine Transform)
encoding. The JPEG image is obtained by a series of steps such as DCT (Discrete Cosine
Transform) transformation, quantization, entropy coding, etc. In this paper, we firstly
transform the images from spatial domain into quaternion domain. By analyzing the
algebraic relationship between QDCT and DCT, a QDCT quantization table and QDTC
coding for color images are proposed. Then the compressed image data is encrypted after
the steps of block permutation, intra-block permutation, single table substitution and stream
cipher. At last, the similarity between original image and query image can be measured by
the Manhattan distance, which is calculated by two feature vectors with the model of bagof -words on the cloud server side. The outcome shows good performance in security attack
and retrieval accuracy.
Keywords
Cite This Article
Q. Ji, P. Yu and Z. Xia, "Qdct encoding-based retrieval for encrypted jpeg images,"
Journal on Big Data, vol. 2, no.1, pp. 33–51, 2020. https://doi.org/10.32604/jbd.2020.01004