一种新的Contourlet域鲁棒水印算法

doi:10.3969/j.issn.1001-2400.2010.02.013

Abstract

Abstract:

In order to improve the robustness and efficiency of the watermark algorithm, a new self-adaptive watermark algorithm based on the texture feature is proposed. This algorithm selects the energy, entropy and contrast of the gray co-occurrence matrix as texture features, rapidly and accurately extracts the strong texture region of host images by the Mean Shift fast clustering algorithm. This algorithm embeds the watermark into the big coefficients in the Contourlet domain of the image strong texture area, adaptively selects the watermark embedding locations and controls the watermark embedding strength through texture clustering outcome. The experiment shows that this algorithm has the strong robustness to the Gauss low pass filter, Wiener filter, median filtering, Salt and pepper noise, Gaussian noise, JPEG compression, shear attack, etc. This algorithm's convergence rate is better than that of both FCM clustering and K-means clustering algorithm. This algorithm has realized blind detection.

Key words: Mean Shift, Contourlet transform, gray level co-occurrence matrix, blind watermark

TONG Ming;FENG Wei;JI Hong-bing. A new robust watermark algorithm in the contourlet domain[J].J4, 2010, 37(2): 254-259.

References

［1］ Wu Jianzhen, Xie Jianyig. Adaptive Image Watermarking Scheme Based on HVS and Fuzzy Clustering Theory［C］//IEEE Int Conf Neural Networks ＆ Signal Processing. Nanjing: IEEE, 2003: 1493-1496.
［2］ El-Khamy S E, El-Yamny N A. A New Perceptual Image Watermarking Technique Based on Adaptive Fuzzy Clustering［C］//21″ National Radio Science Conference (NRSC2004) (NTI). Cairo: IEEE, 2004: 549-556.
［3］ Chang C H, Ye Zhi, Zhang Mingyan. Fuzzy-ART Based Adaptive Digital Watermarking Scheme［J］. IEEE Trans on Circuits and Systems for Video Technology, 2005, 15(1): 65-81.
［4］刘向丽, 寇卫东, 王志国. 一种新的非对称数字水印算法［J］. 西安电子科技大学学报, 2008, 35(1): 129-132.
Liu Xiangli, Kou Weidong, Wang Zhiguo. Asymmetric Digital Watermarking Algorithm Based on DHT［J］. Journal of Xidian University, 2008, 35(1): 129-132.
［5］ Rao S, Liu Weifeng, Principe J C, et al. Information Theoretic Mean Shift Algorithm［C］//Machine Learning for Signal Processing, 2006. Proceedings of the 2006 16th IEEE Signal Processing Society Workshop. Maynooth: IEEE, 2006: 155-160..
［6］ Zhou H, Schaefer G, Sadka A H, et al. Anisotropic Mean Shift Based Fuzzy C-Means Segmentation of Dermoscopy Images［J］. IEEE Journal of Selected Topics in Signal Processing, 2009, 3(1): 26-34.
［7］ Li P. An Adaptive Binning Color Model for Mean Shift Tracking［J］. IEEE Trans on Circuits and Systems for Video Technology, 2008, 18(9): 1293-1299.
［8］ Do M N, Vetterli M. The Contourlet Transform: an Efficient Directional Multiresolution Image Representation［J］. IEEE Trans on Processing, 2005, 14(12): 2091-2106.
［9］ Haralick R M, Shanmugam K, Dinstein I. Textural Features for Image Classification［J］. IEEE Trans on Systems, Man and Cybernetics, 1973, 3(6): 610-621.
［10］ Wen Zhiqiang, Cai Zixing. Convergence Analysis of Mean Shift Algorithm［J］. Journal of Software, 2007, 18(2): 205-212.

[1]	XIN Fangfang;JIAO Licheng;WANG Lingxia;WANG Guiting. Change detection in multitemporal remote sensing images based on local mean dynamic Fisher discriminant analysis [J]. J4, 2012, 39(5): 12-17+29.
[2]	YANG Zhenping;NIU Haijun;DING Lei. New image super-resolution restoration method by NSCT [J]. J4, 2012, 39(1): 34-37+85.
[3]	CUI Lingling;LU Zhaoyang;LI Jing;LI Yihong. Novel algorithm for automated detection of fabric defect images [J]. J4, 2011, 38(5): 65-72.
[4]	GAO Guo-wang;LIU Shang-qian;QIN Han-lin. Robustness-tracking algorithm for the infrared target under complex background noise [J]. J4, 2010, 37(6): 1098-1102.
[5]	HUO Guan-ying;LI Qing-wu;SHI Dan. Multi-sensor image fusion algorithm considering neighborhood consistency in the nonsubsampled contourlet transform domain [J]. J4, 2010, 37(4): 770-776.
[6]	ZHANG Qi;CAO Qi;WANG Xiao-wei;BI Du-yan. Novel IR target tracking method based on the grey prediction and HOGI feature [J]. J4, 2010, 37(4): 751-757.
[7]	JIA Jian1;2;JIAO Li-cheng1. Image denoising using the directional property in the NSCT domain [J]. J4, 2009, 36(2): 269-273.
[8]	SUN Qiang;JIAO Li-cheng;HOU Biao. SAR image despeckling using statistical priors in nonsubsampled contourlet transform domain [J]. J4, 2008, 35(1): 14-21.
[9]	YANG Shui-shan1;HE Yong-hui2;ZHAO Wan-sheng1;PENG Tie-gen2. Application of the Mean shift algorithm in steel strip image segmentation [J]. J4, 2007, 34(6): 1015-1018.
[10]	SUN Wen-fang;SONG Bei-bei;ZHAO Yi-gong. Application of joint Contourlet and Bandelet transforms in image compression [J]. J4, 2007, 34(4): 611-615.
[11]	ZHUANG Huai-yu;WU Cheng-ke;LI Yun-song. A blind image watermarking based on zerotree wavelet [J]. J4, 2004, 31(4): 513-517.

A new robust watermark algorithm in the contourlet domain

PDF (PC)

Like

Knowledge

Cited

Abstract

Cite this article

share this article

References

Related Articles 11

Metrics

Comments

Recommended 0