计算机应用 ›› 2014, Vol. 34 ›› Issue (8): 2361-2364.DOI: 10.11772/j.issn.1001-9081.2014.08.2361

• 计算机安全 • 上一篇    下一篇

用于医学影像快速篡改检测和恢复的无损水印算法

刘定军1,2,陈志刚1,2,邓小鸿1,2,3   

  1. 1. 中南大学 “移动医疗”教育部—中国移动联合实验室,长沙410012;
    2. 中南大学 软件学院,长沙410012
    3. 江西理工大学 应用科学学院,江西 赣州341000
  • 收稿日期:2014-03-10 修回日期:2014-04-16 出版日期:2014-08-01 发布日期:2014-08-10
  • 通讯作者: 陈志刚
  • 作者简介:刘定军(1990-),男,湖南衡阳人,硕士研究生,主要研究方向:图像数据隐藏算法、数字水印;陈志刚(1964-),男,湖南长沙人,教授,博士,CCF会员,主要研究方向:网络与分布式计算;邓小鸿(1982-),男,江西赣州人,讲师,博士,主要研究方向:软件工程、医学图像处理。
  • 基金资助:

    湖南省科技厅重点项目

Quick tampering detection and recovering algorithm based on reversible watermark in medical images

LIU Dingjun1,2,CHEN Zhigang1,2,DENG Xiaohong1,2,3   

  1. 1. School of Software, Central South University, Changsha Hunan 410012, China;
    2. “Mobile Health” Ministry of Education—China Mobile Joint Laboratory, Central South University, Changsha Hunan 410012, China;
    3. College of Applied Science, Jiangxi University of Science and Technology, Ganzhou Jiangxi 341000, China
  • Received:2014-03-10 Revised:2014-04-16 Online:2014-08-01 Published:2014-08-10
  • Contact: CHEN Zhigang

摘要:

针对现有方法中篡改检测效率不高、定位不精确的问题,提出了一种基于无损水印和四叉树分解的医学图像快速篡改检测及恢复的方法。利用对医学图像进行四叉树分解过程中的层次结构特点,提高了篡改检测精确性和定位速度;同时使用分解后块中对角线像素均值作为恢复特征值,保证篡改后图像的修复质量。实验结果表明,与现有方法相比,所提方法在尺寸为512×512的图像中,定位比较次数降至6.7次左右,篡改定位精确性提高了5%左右。

Abstract:

Aiming at the problem of low efficiency of tampering detection and accuracy of location, a medical image tampering detection and recovering method based on reversible watermark and quad-tree decomposition was proposed. The algorithm has higher accuracy and faster tampering location speed by using the hierarchical structure of the quad-tree in the decomposition of the medical images. The method used the diagonal pixel mean in the block as the recovered feature value, which ensures the recovery quality of tampered image. The experimental results show that compared with the existed methods, the proposed algorithm reduces the comparing times for locating tampered region to about 6.7 in the 512×512 images and improves the tampering detection accuracy about 5%.

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