应用科学学报 ›› 2018, Vol. 36 ›› Issue (4): 628-634.doi: 10.3969/j.issn.0255-8297.2018.04.006

• 信号与信息处理 • 上一篇    下一篇

基于动态BoW模型的密文JPEG图像检索

韦秋含, 梁海华, 张新鹏   

  1. 上海大学 通信与信息工程学院, 上海 200444
  • 收稿日期:2017-02-21 修回日期:2017-06-03 出版日期:2018-07-31 发布日期:2018-07-31
  • 通信作者: 张新鹏,教授,博导,研究方向:多媒体信息安全,E-mail:xzhang@shu.edu.cn E-mail:xzhang@shu.edu.cn
  • 基金资助:
    国家自然科学基金(No.U1636206,No.61525203,No.61502009,No.61472235);上海市自然科学基金(No.16ZR1413100);上海市浦江人才计划基金(No.13PJ1403200);上海市曙光学者计划基金(No.14SG36);上海市优秀学术带头人计划基金(No.16XD1401200)资助

Encrypted JPEG Image Retrieval Based on Dynamic BoW Model

WEI Qiu-han, LIANG Hai-hua, ZHANG Xin-peng   

  1. School of Communication and Information Engineering, Shanghai University, Shanghai 200444, China
  • Received:2017-02-21 Revised:2017-06-03 Online:2018-07-31 Published:2018-07-31

摘要: 为了实现高效的密文JPEG图像检索,提出了一种基于加密图像AC系数统计直方图的动态检索方案.首先,根据密文图像的AC系数采用自适应k-均值聚类构建动态词袋(bag-of-word,BoW)模型.其次,借助BoW模型将图像块的AC系数统计特征转化为全局直方图特征.最后,由服务器根据直方图特征来判断相似性,从而提高检索效率.即使密文图像库动态更新,如密文图像的新增与删除,该检索方案也是鲁棒高效的.实验结果表明,该方案在保证检索准确度的同时大大提高了检索效率,具有实际应用价值.

关键词: 密文JPEG图像检索, 词袋模型, 自适应k-均值聚类, 动态更新

Abstract: This paper presents an efficient and dynamic retrieval scheme for encrypted JPEG images, which is based on the histogram of AC coefficients. First, the robust bagof-word (BoW) model is constructed in the encrypted domain via the advanced k-means clustering. Second, the local features of images are transformed into the global statistical histograms by the dynamic BoW model. Finally, the cloud server uses the histograms of the encrypted images to judge similarity. Besides, dynamic update operations like insertion and deletion of images are also available, so the retrieval scheme is still robust and efficient. The results of experiments show that the proposed scheme can improve the retrieval efficiency and ensure the accuracy of retrieval at the same time, having practical application value.

Key words: encrypted JPEG image retrieval, adaptive k-means clustering, dynamic update, bag-of-word model

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