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
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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.
Xiong Neal N.
中科院分区:
计算机科学3区
文献类型:
--
作者:
Qin Jiaohua;Li Hao;Xiang Xuyu;Tan Yun;Pan Wenyan;Pan Wentao;Ma Wentao;Xiong Neal N.

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云计算中的加密图像检索是实现海量图像存储管理和图像安全的关键技术。提出了一种用于加密图像检索的特征提取方法。首先,利用改进的Harris算法提取图像特征;然后,利用加速鲁棒特征算法和Bag of Words模型生成每张图像的特征向量。然后,采用局部敏感哈希算法构建特征向量的可搜索索引;采用混沌加密方案对图像和索引进行安全保护。最后,在云服务器上执行安全相似度搜索。实验结果表明,与现有的加密检索方案相比,所提出的检索方案不仅减少了时间消耗,而且提高了图像检索的精度。
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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