Novel ROI watermarking scheme combined with the behavior of primary visual cortex

被引:0
|
作者
Lü W.-L. [1 ]
Guo Y.-T. [1 ,2 ]
Luo B. [1 ]
机构
[1] School of Computer Science and Technology, Anhui University
[2] Computer Department, Anhui Institute of Education
关键词
Berkeley wavelet transform; ICA; ROI; Watermarking;
D O I
10.3969/j.issn.1001-0548.2011.06.021
中图分类号
学科分类号
摘要
If obvious objects in an image are deleted, the image would be meaningless. The protection of the image contents is imminence. A novel image watermarking scheme combined with the behavior of primary visual cortex is proposed. The Berkeley wavelet transform shares many characteristics with the receptive fields of neurons in mammalian primary visual cortex (V1). The watermark is embedded into the region-of-interest (ROI) position of an image. Independent component analysis (ICA) is adapted to the watermark extraction procedure and the original image is not necessary. Experimental results demonstrate that the proposed watermarking technique successfully locates ROI position automatically, has a good vision performance and robustness against some attacks as JPEG compress, noises, and little rotation and scale, luminance and contrast enhancement and low pass filtering. More importantly, the proposed scheme can extract the watermarks with high quality even if majority background of an original image is removed.
引用
收藏
页码:915 / 920
页数:5
相关论文
共 11 条
  • [1] Schneider M., Chang S.F., A robust content based digital signature for image authentication, Proceedings of IEEE International Conference on Image Processing, pp. 227-230, (1996)
  • [2] Fridrich J., Goljan M., Images with self-correcting capabilities, Proceedings of IEEE International Conference on Image Processing, pp. 792-796, (1999)
  • [3] Lin C.Y., Chang S.F., Semifriagile watermarking for authenticating JPEG visual content, Proceedings of SPIE, Security and Watermarking of Multimedia Contents II, pp. 140-151, (2000)
  • [4] Zhang L., Xiao W., Qian G., Et al., Rotation, scaling, and translation invariant local watermarking technique with Krawtchouk moments, Chinese Optics Letters, 5, 1, pp. 21-24, (2007)
  • [5] Bas P., Chassery J.M., Macq B., Geometrically invariant watermarking using feature points, IEEE Transantions on Image Processing, 11, 9, pp. 1014-1028, (2002)
  • [6] Tang C.W., Hang H.M., A feature-based robust digital image watermarking scheme, IEEE Transactions on Signal Processing, 51, 4, pp. 950-959, (2003)
  • [7] Wang X., Wu J., Niu P., A new digital image watermarking algorithm resilient to desynchronization attacks, IEEE Transantions on Information Forensics and Security, 2, 4, pp. 655-663, (2007)
  • [8] Wang X.Y., Hou L.M., Wu J., Feature-based digital image watermarking scheme robust to geometric attacks, Acta Automatica Sinica, 34, 1, pp. 1-6, (2008)
  • [9] Willmore B., Prenger R.J., Wu M.C.K., Et al., The Berkeley wavelet transform: a biologically inspired orthogonal wavelet transform, Neural Computation, 20, 6, pp. 1537-1564, (2008)
  • [10] Siagian C., Itti L., Rapid biologically-inspired scene classification using features shared with visual attention, IEEE Transactions on Pattern Analysis and Machine Intelligence, 29, 2, pp. 300-312, (2007)