A Content-based Image Retrieval Scheme Using Compressible Encrypted Images

Iida, Koji; Kiya, Hitoshi

doi:10.23919/eusipco47968.2020.9287671

Cited by 7 publications

(5 citation statements)

References 31 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Privacy-preserving image retrieval applications: The CPE scheme's cipher images preserve the image local contents on a block level; this information can be exploited for image retrieval applications without revealing the visual information of the image, as demonstrated in [57][58][59][60]. To achieve security, they used a Color CPE scheme with the JPEG and JPEG-LS standards.…”

Section: Cpe Scheme Applicationsmentioning

confidence: 99%

Comprehensive Analysis of Compressible Perceptual Encryption Methods—Compression and Encryption Perspectives

Ahmad

Choi

Shin

2023

Sensors

View full text Add to dashboard Cite

Perceptual encryption (PE) hides the identifiable information of an image in such a way that its intrinsic characteristics remain intact. This recognizable perceptual quality can be used to enable computation in the encryption domain. A class of PE algorithms based on block-level processing has recently gained popularity for their ability to generate JPEG-compressible cipher images. A tradeoff in these methods, however, is between the security efficiency and compression savings due to the chosen block size. Several methods (such as the processing of each color component independently, image representation, and sub-block-level processing) have been proposed to effectively manage this tradeoff. The current study adapts these assorted practices into a uniform framework to provide a fair comparison of their results. Specifically, their compression quality is investigated under various design parameters, such as the choice of colorspace, image representation, chroma subsampling, quantization tables, and block size. Our analyses have shown that at best the PE methods introduce a decrease of 6% and 3% in the JPEG compression performance with and without chroma subsampling, respectively. Additionally, their encryption quality is quantified in terms of several statistical analyses. The simulation results show that block-based PE methods exhibit several favorable properties for the encryption-then-compression schemes. Nonetheless, to avoid any pitfalls, their principal design should be carefully considered in the context of the applications for which we outlined possible future research directions.

show abstract

Section: Cpe Scheme Applicationsmentioning

confidence: 99%

Comprehensive Analysis of Compressible Perceptual Encryption Methods—Compression and Encryption Perspectives

Ahmad

Choi

Shin

2023

Sensors

View full text Add to dashboard Cite

show abstract

“…The Encryption alongside Compression methodology was proffered by [11] for retrieving images safely.…”

Section: Literature Surveymentioning

confidence: 99%

Triplet Label Based Image Retrieval Using Deep Learning in Large Database

Nithya¹,

Rajamani²

2023

Computer Systems Science and Engineering

View full text Add to dashboard Cite

Recent days, Image retrieval has become a tedious process as the image database has grown very larger. The introduction of Machine Learning (ML) and Deep Learning (DL) made this process more comfortable. In these, the pair-wise label similarity is used to find the matching images from the database. But this method lacks of limited propose code and weak execution of misclassified images. In order to get-rid of the above problem, a novel triplet based label that incorporates context-spatial similarity measure is proposed. A Point Attention Based Triplet Network (PABTN) is introduced to study propose code that gives maximum discriminative ability. To improve the performance of ranking, a correlating resolutions for the classification, triplet labels based on findings, a spatialattention mechanism and Region Of Interest (ROI) and small trial information loss containing a new triplet cross-entropy loss are used. From the experimental results, it is shown that the proposed technique exhibits better results in terms of mean Reciprocal Rank (mRR) and mean Average Precision (mAP) in the CIFAR-10 and NUS-WIPE datasets.

show abstract

“…In the second approach, descriptors are directly extracted from encrypted images by a cloud provider as well as for plain images [12]- [17], where each data owner only encrypts images. In addition, data owners and users do not need to share keys.…”

Section: ) Generating Descriptors From Encrypted Imagesmentioning

confidence: 99%

“…The proposed retrieval scheme corresponds to this approach. Schemes [12]- [17] are carried out the basis on this approach. Some schemes [15], [16] consider compressing images with JPEG, but their retrieval performance will be degraded due to the difference in coding parameters used for JPEG compression.…”

Section: ) Generating Descriptors From Encrypted Imagesmentioning

confidence: 99%

“…Some schemes [15], [16] consider compressing images with JPEG, but their retrieval performance will be degraded due to the difference in coding parameters used for JPEG compression. On the other hand, a scheme using extended SIMPLE descriptors extracted from EtC images does not have the limitation [17]. However, the mixed use of plain images and encrypted ones have never considered yet in this scheme.…”

Section: ) Generating Descriptors From Encrypted Imagesmentioning

confidence: 99%

See 1 more Smart Citation

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

Iida

Kiya

2020

IEEE Access

Self Cite

View full text Add to dashboard Cite

In this paper, we propose a novel content basedimage retrieval scheme allowing the mixed use of encrypted and plain images for the first time. In the proposed scheme, images are encrypted by a block-scrambling method developed for encryption-then-compression (EtC) systems. The encrypted images, referred to as EtC images, can be compressed with JPEG, as well as for plain images. Image descriptors used for the proposed retrieval is designed to avoid the effect of image encryption. As a result, the use of EtC images and the descriptors allows us to carry out retrieval of both encrypted images and plain ones. In an experiment, the proposed scheme is demonstrated to have the same performance as conventional retrieval methods with plain images, even under the mixed use of plain images and EtC ones.

show abstract

A Content-based Image Retrieval Scheme Using Compressible Encrypted Images

Cited by 7 publications

References 31 publications

Comprehensive Analysis of Compressible Perceptual Encryption Methods—Compression and Encryption Perspectives

Comprehensive Analysis of Compressible Perceptual Encryption Methods—Compression and Encryption Perspectives

Triplet Label Based Image Retrieval Using Deep Learning in Large Database

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

Contact Info

Product

Resources

About