A Novel Content Based Image Retrieval Scheme in Cloud Computing

2019 ◽  
pp. 606-616
Author(s):  
Zhuohua Liu ◽  
Caijuan Huang ◽  
Hui Suo ◽  
Bin Yang
Keyword(s):  
Cloud Computing ◽  
Image Retrieval ◽  
Content Based Image Retrieval ◽  
Retrieval Scheme

A Privacy-Preserving and Copy-Deterrence Content-Based Image Retrieval Scheme in Cloud Computing

2016 ◽  
Vol 11 (11) ◽  
pp. 2594-2608 ◽  
Author(s):  
Zhihua Xia ◽  
Xinhui Wang ◽  
Liangao Zhang ◽  
Zhan Qin ◽  
Xingming Sun ◽  
...  
Keyword(s):  
Cloud Computing ◽  
Image Retrieval ◽  
Privacy Preserving ◽  
Content Based Image Retrieval ◽  
Retrieval Scheme

BOEW: A Content-based Image Retrieval Scheme using Bag-of-Encrypted-Words in Cloud Computing

2019 ◽  
pp. 1-1 ◽  
Author(s):  
Zhihua Xia ◽  
Leqi Jiang ◽  
Dandan Liu ◽  
Lihua Lu ◽  
Byeungwoo Jeon
Keyword(s):  
Cloud Computing ◽  
Image Retrieval ◽  
Content Based Image Retrieval ◽  
Retrieval Scheme

scholarly journals A Content-Based Image Retrieval Scheme Using an Encrypted Difference Histogram in Cloud Computing

Information ◽  
2017 ◽  
Vol 8 (3) ◽  
pp. 96 ◽  
Author(s):  
Dandan Liu ◽  
Jian Shen ◽  
Zhihua Xia ◽  
Xingming Sun
Keyword(s):  
Cloud Computing ◽  
Image Retrieval ◽  
Content Based Image Retrieval ◽  
Retrieval Scheme ◽  
Difference Histogram

EPCBIR: An efficient and privacy-preserving content-based image retrieval scheme in cloud computing

2017 ◽  
Vol 387 ◽  
pp. 195-204 ◽  
Author(s):  
Zhihua Xia ◽  
Neal N. Xiong ◽  
Athanasios V. Vasilakos ◽  
Xingming Sun
Keyword(s):  
Cloud Computing ◽  
Image Retrieval ◽  
Privacy Preserving ◽  
Content Based Image Retrieval ◽  
Retrieval Scheme

Towards Privacy-Preserving Content-Based Image Retrieval in Cloud Computing

2018 ◽  
Vol 6 (1) ◽  
pp. 276-286 ◽  
Author(s):  
Zhihua Xia ◽  
Yi Zhu ◽  
Xingming Sun ◽  
Zhan Qin ◽  
Kui Ren
Keyword(s):  
Cloud Computing ◽  
Image Retrieval ◽  
Privacy Preserving ◽  
Content Based Image Retrieval

A FAST TWO-STAGE CONTENT-BASED IMAGE RETRIEVAL APPROACH IN THE DCT DOMAIN

2008 ◽  
Vol 22 (04) ◽  
pp. 765-781 ◽  
Author(s):  
TIENWEI TSAI ◽  
YO-PING HUANG ◽  
TE-WEI CHIANG
Keyword(s):  
Image Retrieval ◽  
High Efficiency ◽  
Feature Space ◽  
Content Based Image Retrieval ◽  
Two Stage ◽  
Feature Extraction Method ◽  
Domain Specific ◽  
Retrieval Scheme ◽  
Domain Specific Knowledge ◽  
Distinct Features

In this paper, a two-stage content-based image retrieval (CBIR) approach is proposed to improve the retrieval performance. To develop a general retrieval scheme which is less dependent on domain-specific knowledge, the discrete cosine transform (DCT) is employed as a feature extraction method. In establishing the database, the DC coefficients of Y, U and V components are quantized such that the feature space is partitioned into a finite number of grids, each of which is mapped to a grid code (GC). When querying an image, at coarse classification stage, the grid-based classification (GBC) and the distance threshold pruning (DTP) serve as a filter to remove those candidates with widely distinct features. At the fine classification stage, only the remaining candidates need to be computed for the detailed similarity comparison. The experimental results show that both high efficacy and high efficiency can be achieved simultaneously using the proposed two-stage approach.

Images Retrieval Based on Integrated Features

2014 ◽  
Vol 543-547 ◽  
pp. 2292-2295
Author(s):  
Ching Hung Su ◽  
Huang Sen Chiu ◽  
Mohd Helmy A. Wahab ◽  
Tsai Ming Hsiehb ◽  
You Chiuan Li ◽  
...  
Keyword(s):  
Image Retrieval ◽  
Retrieval System ◽  
Texture Feature ◽  
Content Based Image Retrieval ◽  
Code Comparison ◽  
Retrieval Scheme ◽  
Image Retrieval System ◽  
Retrieval Problem ◽  
Color Sequence ◽  
Edge Histogram

We propose a practical image retrieval scheme to retrieve images efficiently. The proposed scheme transfers each image to a color sequence using straightforward 8 rules. Subsequently, using the color sequences to compare the images, namely color sequences comparison. We succeed in transferring the image retrieval problem to sequences comparison and subsequently using the color sequences comparison along with the texture feature of Edge Histogram Descriptor to compare the images of database. We succeed in transferring the image retrieval problem to quantized code comparison. Thus the computational complexity is decreased obviously. Our results illustrate it has virtues both of the content based image retrieval system and a text based image retrieval system.

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