ABSTRACT:
Content-based image retrieval (CBIR)
applications have been rapidly developed along with the increase in the
quantity, availability and importance of images in our daily life. However, the
wide deployment of CBIR scheme has been limited by its the severe computation
and storage requirement. In this paper, we propose a privacy-preserving
content-based image retrieval scheme, which allows the data owner to outsource
the image database and CBIR service to the cloud, without revealing the actual
content of the database to the cloud server. Local features are utilized to
represent the images, and earth mover’s distance (EMD) is employed to evaluate
the similarity of images. The EMD computation is essentially a linear
programming (LP) problem. The proposed scheme transforms the EMD problem in
such a way that the cloud server can solve it without learning the sensitive
information. In addition, local sensitive hash (LSH) is utilized to improve the
search efficiency. The security analysis and experiments show the security and
efficiency of the proposed scheme.
SYSTEM REQUIREMENTS:
HARDWARE REQUIREMENTS:
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System : Pentium Dual Core.
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Hard Disk : 120 GB.
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Monitor : 15’’ LED
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Input Devices : Keyboard, Mouse
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Ram : 1 GB
SOFTWARE REQUIREMENTS:
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Operating system : Windows 7.
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Coding Language : JAVA/J2EE
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Tool : Netbeans 7.2.1
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Database : MYSQL
REFERENCE:
Zhihua Xia, Member, IEEE, Yi Zhu, Xingming Sun, Senior Member, IEEE, Zhan Qin, Member, IEEE and Kui Ren, Senior Member, IEEE, “Towards
Privacy-preserving Content-based Image Retrieval in Cloud Computing”, IEEE
Transactions on Cloud Computing, 2018