An Encrypted Image Retrieval Method Based on Harris Corner Optimization and LSH in Cloud Computing
An Encrypted Image Retrieval Method Based on Harris Corner Optimization and LSH in Cloud Computing
复制标题
云计算中基于Harris角点优化和LSH的加密图像检索方法
DOI:
10.1109/access.2019.2894673
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发表时间:
2019-01
期刊:
影响因子:
3.9
通讯作者:
Xiong Neal N.
中科院分区:
文献类型:
--
作者:
Qin Jiaohua;Li Hao;Xiang Xuyu;Tan Yun;Pan Wenyan;Pan Wentao;Ma Wentao;Xiong Neal N.
The encrypted image retrieval in cloud computing is a key technology to realize the massive images of storage and management and images safety. In this paper, a novel feature extraction method for encrypted image retrieval is proposed. First, the improved Harris algorithm is used to extract the image features. Next, the Speeded-Up Robust Features algorithm and the Bag of Words model are applied to generate the feature vectors of each image. Then, Local Sensitive Hash algorithm is applied to construct the searchable index for the feature vectors. The chaotic encryption scheme is utilized to protect images and indexes security. Finally, secure similarity search is executed on the cloud server. The experimental results show that compared with the existing encryption retrieval schemes, the proposed retrieval scheme not only reduces the time consumption but also improves the image retrieval accuracy.
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DOI:
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IEICE Trans. Inf. Syst.
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