收稿日期: 2018-01-28
网络出版日期: 2018-03-31
基金资助
国家自然科学基金面上项目（No.41571426）；国家重点研发计划项目基金（No.2017YFB0504202）；武汉市应用基础研究计划项目基金（No.2017010201010114）资助
A Secure Image Retrieval Method Based on Combined Orthogonal Decomposition and BoVW
Received date: 2018-01-28
Online published: 2018-03-31
当前云平台下加密域图像检索存在特定加密算法而不能满足不同应用需求，并且需依靠底层图像特征进行检索，从而导致精度较低，为此提出了一种结合正交分解和视觉词袋模型（BoVW）的图像安全检索方法.引入正交分解框架，将图像数据域分为加密域和检索域，使得加密操作和特征提取操作相互独立，避免加密和特征提取操作相互影响.在加密域用户可以根据需要选择合适的加密方法；在检索域引入视觉词袋模型框架，将图像表示为视觉单词直方图，降低底层特征与高层语义之间存在的语义鸿沟，提高检索精度.实验结果显示，与当前加密域图像检索技术相比，该方法具有更高的安全性和检索精准度，能在云环境下更好地保护图像数据的隐私，且实用性较好.
赵啸, 徐彦彦, 龚佳颖, 宋方振 . 一种结合正交分解及BoVW的图像安全检索方法[J]. 应用科学学报, 2018 , 36(2) : 299 -308 . DOI: 10.3969/j.issn.0255-8297.2018.02.009
We propose an image security retrieval method combining orthogonal decomposition and bag of visual word model (BoVW) in this paper to solve the problems that existing encryption algorithms for the current encryption domain image retrieval cannot meet the needs of different applications, and the algorithms relying on underlying image generally suffer lower retrieval accuracy. By introducing orthogonal decomposition framework, the image data domain is divided into the encryption domain and the retrieval domain. The encryption operation and feature extraction operation are independent, without interaction between them. In the encryption domain, users can choose any encryption method as needed. In the retrieval domain, the visual word bag model framework is introduced, and the image is represented as the visual word histogram, which reduces the semantic gap between the underlying feature and the high-level semantics, accordingly, improving the retrieval precision. Experimental results show that the proposed method provides higher security and higher retrieval precision than the current encryption domain image retrieval techniques.
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