计算机科学 ›› 2018, Vol. 45 ›› Issue (9): 195-201.doi: 10.11896/j.issn.1002-137X.2018.09.032

• 信息安全 • 上一篇    下一篇

基于回归型支持向量机的医学图像可视可逆水印算法

王楠, 李智, 程欣宇, 陈怡   

  1. 贵州省智能医学影像分析与精准诊断重点实验室 贵阳550025
    贵州大学计算机科学与技术学院 贵阳550025
  • 收稿日期:2018-06-30 出版日期:2018-09-20 发布日期:2018-10-10
  • 通讯作者: 李 智(1977-),女,博士,副教授,CCF会员,主要研究领域为医学影像分析、图像处理、视频信息安全、机器学习等,E-mail:lizhigzu@163.com
  • 作者简介:王 楠(1993-),女,硕士生,主要研究领域为医学影像分析、图形图像处理、信息隐藏;程欣宇(1978-),男,硕士,副教授,CCF会员,主要研究领域为医学影像分析、信息安全、机器学习;陈 怡(1994-),女,硕士生,主要研究领域为医学影像分析、图形图像处理、信息隐藏。
  • 基金资助:
    本文受国家自然科学基金项目(61462013, 61661010),贵州大学引进人才科研项目(2009(009))资助。

Reversible Visible Watermarking Algorithm for Medical Image Based on Support Vector Regression

WANG Nan, LI Zhi, CHENG Xin-yu, CHEN Yi   

  1. Key Laboratory of Intelligent Medical Image Analysis and Precise Diagnosis of Guizhou Province,Guiyang 550025,China
    College of Computer Science and Technology,Guizhou University,Guiyang 550025,China
  • Received:2018-06-30 Online:2018-09-20 Published:2018-10-10

摘要: 随着医学影像技术的发展,医学图像成为医生诊断患者病情的主要依据,为了给患者提供更为准确的诊断和最佳的治疗方案,医学图像共享和专家远程诊断成为重要的诊疗手段。未被保护的医学图像在传输过程中易受到攻击或恶意篡改,为有效保护医学图像信息的完整性并限制未授权用户的使用,提出了一种基于回归型支持向量机的医学图像可视可逆水印算法。该算法首先将可视水印嵌入医学图像中;其次利用回归型支持向量机对水印图像的像素值进行预测,并计算出预测误差,利用纹理度等级自适应确定合适的亮度调节阈值,根据阈值生成一幅全局定位图,将全局定位图加入到原始图像中,以增强算法的鲁棒性;最后利用全局定位图和预测误差之间的相互关系生成一个可视可逆的水印,从而对医学图像进行加密保护。实验结果表明,所提可视可逆算法不仅可应用于传统医学图像,还首次应用于弥散加权图像,且该算法具有较好的鲁棒性和可逆性,能有效避免像素点溢出问题,实现可逆水印的正确提取,提取水印后的图像与原始图像没有任何差异。在水印信息未知的情况下,可视可逆水印去除困难,该特性可有效保护患者信息的完整性和医学图像的权威性。

关键词: 回归型支持向量机, 可视可逆水印, 弥散加权图像, 纹理度, 医学图像

Abstract: With the development of medical imaging technology,medical image has become the main basis for doctors to diagnose patients’ condition.In order to provide more accurate diagnosis and optimal treatment plan for patients,medical image sharing and expert remote diagnosis have become important medical tools.Unprotected medical images are easily attacked or tampered maliciously during transmission,so this paper proposed a reversible visible watermarking algorithm for medical image based on support vector regyession to effectively protect the integrity of medical image information and limit the application of unauthorized users.Firstly,the algorithm embeds the visual watermark into the medi-cal image.Secondly,it uses the support vector regression to forecast the pixel value of the watermark image,and calculates the prediction error.Then,it applies the texture level to determine the appropriate brightness adjustment thre-shold,thus generating a global positioning map according to the threshold,and it adds the global positioning map to the original image to enhance the robustness of the algorithm.Finally,it generates a reversible visual watermark by using the relationship between the global positioning map and the prediction error to encrypt the medical image.The experimental results show that the reversible visible algorithm can be applied to not only traditional medical images,but also diffusion weighted images for the first time.The algorithm has good robustness and reversibility,and can effectively avoid pixel overflow problems,achieving the correct extraction of reversible watermark.There is no any difference between the recovered image and the original image.When the watermark information is unknown,it is difficult to remove visible reversible watermarking,and this feature can effectively protect the integrity of patient information and the authority of medical images.

Key words: Diffusion weighted image, Medical image, Support vector regression, Textural degree, Visible reversible watermark

中图分类号: 

  • TP309
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