广西师范大学学报（自然科学版） ›› 2019, Vol. 37 ›› Issue (2): 90-104.doi: 10.16088/j.issn.1001-6600.2019.02.011

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基于图像插值和参考矩阵的可逆信息隐藏算法

孙容海1, 施林甫1, 黄丽艳2, 唐振军1, 俞春强3*   

  1. 1.广西师范大学广西多源信息挖掘与安全重点实验室,广西桂林541004;
    2.广西师范大学出版社集团,广西桂林541004;
    3.广西师范大学网络信息中心,广西桂林541004
  • 收稿日期:2018-06-25 出版日期:2019-04-25 发布日期:2019-04-28
  • 通讯作者: 俞春强(1988—),男,江西上饶人,广西师范大学助理研究员。E-mail:yu_chunqiang@126.com
  • 基金资助:
    国家自然科学基金(61562007,61762017);广西自然科学基金(2017GXNSFAA198222,2015GXNSFDA139040)

Reversible Data Hiding Based on Image Interpolation and Reference Matrix

SUN Ronghai1, SHI Linfu1, HUANG Liyan2, TANG Zhenjun1, YU Chunqiang3*   

  1. 1.Guangxi Key Lab of Multi-source Information Mining and Security, Guangxi Normal University, Guilin Guangxi 541004, China;
    2.Guangxi Normal University Press(Group), Guilin Guangxi 541004, China;
    3.Network Information Center, Guangxi Normal University, Guilin Guangxi 541004, China
  • Received:2018-06-25 Online:2019-04-25 Published:2019-04-28

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摘要： 本文提出一种基于插值技术和参考矩阵的可逆信息隐藏算法。该算法首先用一种改进的线性插值方法对载体图像进行插值,生成一幅插值图像;然后对插值图像进行不重叠分块,分块大小为2×2,在每个分块中以左上角的像素值作为平面坐标点的横坐标,其他像素值作为纵坐标构造3个坐标点并将其映射到参考矩阵中;最后根据秘密信息的十进制值和参考矩阵中相应坐标点的值来修改纵坐标以实现信息隐藏。在提取秘密信息时,通过信息隐藏时相同方法构造每个分块的3个坐标点并映射到参考矩阵中获取相应坐标点处的值完成秘密信息的提取。由于信息隐藏过程仅修改插值像素,原始像素保持不变,因此可无损还原载体图像。大量实验结果表明,该算法具有较大的信息隐藏容量和较好的视觉效果。

关键词: 图像插值, 线性插值, 可逆信息隐藏, 参考矩阵

Abstract: A reversible data hiding algorithm based on interpolation technique and reference matrix is proposed in this paper. Firstly, the cover image is interpolated to generate an interpolated image using an improved linear interpolation method. Then, the interpolated image is divided into non-overlapped blocks with size 2×2. And the pixel in top-left corner of each block is taken as horizontal ordinate of the point in plane. Moreover, other pixels are taken as vertical ordinates to construct three coordinate points, which are mapped into reference matrix. Finally, the vertical ordinates are modified in accordance with the decimal value of secret data and the value of corresponding coordinate points in reference matrix to realize data hiding. During data extraction, three coordinate points of each block are constructed via the same method in data hiding and mapped into the reference matrix to obtain the values of corresponding coordinate points to achieve data extraction. Since only interpolated pixels are modified and the original pixels keep unchanged, the cover image can be recovered without loss. Experimental results demonstrate that the proposed algorithm reaches high embedding capacity and has good visual quality.

Key words: image interpolation, linear interpolation, reversible information hiding, reference matrix

中图分类号: 

  • TP391
[1] 王宪保,李洁,姚明海,等.基于深度学习的太阳能电池片表面缺陷检测方法[J].模式识别与人工智能,2014,27(6): 517-523.DOI:10.16451/j.cnki.issn1003-6059.2014.06.006.
[2] JIA Hongbin,MURPHEY Y L,SHI Jianjun.An intelligent real-time vision system for surface defect detection[C]//Proceedings of the 17th International Conference on Pattern Recognition.Los Alamitos,CA:IEEE Computer Society Press,2004:239-242.DOI: 10.1109/ICPR.2004.1334512.
[3] PENG Xiangqian,CHEN Youping,YU Wenyong,et al.An online defects inspection method for float glass fabrication based on machine vision[J].International Journal of Advanced Manufacturing Technology,2008,39(11/12):1180-1189. DOI:10.1007/s00170-007-1302-7.
[4] 胡浩,梁晋,唐正宗,等.数字图像相关法测量金属薄板焊接的全场变形[J].光学精密工程, 2012,20(7):1636-1644.DOI:10.3788/OPE.20122007.1636.
[5] 卜雄洙,李桂娟,杨波,等.中心偏移的全景环形图像快速展开[J].光学精密工程,2012,20(9):2103-2109.DOI: 10.3788/OPE.20122009.2103.
[6] JIAN Chuanxia,GAO Jian,AO Yinhui.Automatic surface defect detection for mobile phone screen glass based on machine vision[J].Applied Soft Computing,2017,52:348-358.DOI: 10.1016/j.asoc.2016.10.030.
[7] LU Chijie,TSAI Duming.Independent component analysis-based defect detection in patterned liquid crystal display surfaces[J].Image and Vision Computing,2008,26(7):955-970.DOI:10.1016/j.imavis.2007.10.007.
[8] ZHANG Lei,GRIFT T E.A new approach to crop-row detection in corn[C]//American Society of Agricultural and Biological Engineers Annual International Meeting 2010.St. Joseph,MI:American Society of Agricultural and Biological Engineers,2010:3950-3964.DOI:10.13031/2013.29834.
[9] SUN T H,TSENG C C,CHEN M S.Electric contacts inspection using machine vision[J].Image and Vision Computing, 2010, 28(6):890-901.DOI:10.1016/j.imavis.2009.11.006.
[10] 王震宇.基于机器视觉钢板表面缺陷检测技术研究[J].计算机与现代化,2013(7):130-134.DOI:10.3969/j.issn. 1006-2475.2013.07.035.
[11] 李超,孙俊.基于机器视觉方法的焊缝缺陷检测及分类算法[J].计算机工程与应用,2018,54(6):264-270.DOI: 10.3778/j.issn.1002-8331.1609-0322.
[12] 黄志鸿,毛建旭,王耀南,等.基于机器视觉的啤酒瓶口缺陷检测分类方法研究[J].电子测量与仪器学报,2016,30(6):873-879.DOI:10.13382/j.jemi.2016.06.006.
[13] 杨洋.基于SVM的印刷品缺陷在线检测[D].武汉:华中科技大学,2012.
[14] 孙智权,周奇,陈震,等.基于CMOS图像传感器的太阳能电池缺陷检测系统设计[J].仪表技术与传感器,2018(1):60-63.DOI:10.3969/j.issn.1002-1841.2018.01.015.
[15] 刘焕军,王耀南,段峰.基于支撑向量机的空瓶智能检测方法[J].控制与决策,2005,20(12):1434-1437.DOI:10.13195/j.cd.2005.12.116.liuhj.026.
[16] 贾云得.机器视觉[M].北京:科学出版社, 2000:48-81.
[17] 贺秋伟,王龙山,于忠党,等.基于图像处理和支持向量机的微型齿轮缺陷检测[J].吉林大学学报(工学版),2008,38(3):565-569.DOI:10.13229/j.cnki.jdxbgxb2008.03.008.
[18] KEERTHIS S,LIN C J.Asymptotic behaviors of support vector machines with Gaussian kernel[J].Neural Computation, 2003,15(7):1667-1689.DOI:10.1162/089976603321891855.
[19] 吴彰良,孙长库,刘洁.基于支持向量机的油封缺陷图像检测方法[J].光电工程,2012,39(3):40-45.DOI:10.3969/j.issn.1003-501X.2012.03.008.
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