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| Image Steganography Algorithm Based on Visual Attention and Local Complexity |
| KANG Nian-Jin,CHEN Zhao-Jiong |
| College of Mathematics and Computer Science,Fuzhou University,Fuzhou 350108 |
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Abstract Visual attention is an important characteristic in the human perception system. However,most visual perception based steganography algorithms consider low-level factors only,such as brightness,contrast and masking effect. A gray image steganography algorithm is proposed based on visual attention and local complexity. The local complexity of the image is analyzed by standard deviation algorithm. Then,the Itti visual attention model is introduced into more complex areas,and the attention characteristics are quantitatively identified by visual entropy. Finally,the steganography is implemented by LSB method on different image blocks segmented through the hierarchies of visual attention and local complexity. The experimental results show that the proposed algorithm maintains good imperceptibility after embedding large-capacity information and resists the histogram contrast steganalysis.
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Received: 21 May 2012
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[1] Gao Xinbo,Lu Wen,Tao Dacheng,et al. Image Quality Assessment and Human Visual System // Proc of the Visual Communications and Image Processing. Huangshan,China,2010: 1-10
[2] You Junyong,Perkis A,Gabbouj M. Improving Image Quality Assessment with Modeling Visual Attention // Proc of the 2nd European Workshop on Visual Information Processing. Paris,France,2010: 177- 182
[3] Afrokhteh M,Ibrahim S. Adaptive Steganography Scheme Using More Surrounding Pixels // Proc of the International Conference on Computer Design and Applications. Qinhuangdao,China,2010,Ⅰ: 225-229
[4] Lou D C,Wu N I,Wang C M,et al. A Novel Adaptive Steganography Based on Local Complexity and Human Vision Sensitivity. Journal of Systems and Software,2010,83(7): 1236-1248
[5] Hsiao J Y,Chang C T. An Adaptive Steganographic Method Based on the Measurement of Just Noticeable Distortion Profile. Image and Vision Computing,2011,29(2/3): 155-166
[6] Zhang Libao,Ma Xinyue,Chen Qi. Image Zero-Watermarking Algorithm Based on Region of Interest. Journal on Communications,2009,30(S2): 117-120 (in Chinese)
(张立保,马新悦,陈 琪.基于感兴趣区的图像零水印算法.通信学报,2009,30(S2): 117- 120)
[7] Kundu M K,Das S. Lossless ROI Medical Image Watermarking Technique with Enhanced Security and High Payload Embedding // Proc of the 20th International Conference on Pattern Recognition. Istanbul,Turkey,2010: 1457-1460
[8] Wang Yan,Liang Dequn,Wang Yanchun,et al. Image Characteristics-Based Coiflet Domain Digital Watermarking Algorithm. Acta Electronica Sinica,2006,34(12): 2214-2217 (in Chinese)
(王 演,梁德群,王彦春,等.基于图像属性的Coiflet域数字水印算法.电子学报,2006,34(12): 2214-2217)
[9] LO-Varco G,Puech W. DCT-Based Data Hiding for Securing ROI of Color Images // Proc of the IEEE International Conference on Image Processing. Genova,Italy,2005,Ⅱ: 1086 -1089
[10] Han Chengmei,Lü Wanli,Luo Bin. Regions of Interest Watermarking Based on Tchebichef Moment. Computer Engineering and Design,2011,32(5): 1585-1588 (in Chinese)
(韩成美,吕皖丽,罗 斌.基于Tchebichef矩的感兴趣区水印.计算机工程与设计,2011,32(5): 1585-1588)
[11] Kang Nianjin,Chen Zhaojiong. Large-Capacity Blind Steganography Algorithm for Color Images Based on Visual Perception Mechanism.Journal of Computer Applications,2012,32(9): 2568-2572(in Chinese)
(康年锦,陈昭炯.基于视觉感知机理的大容量彩色图像盲隐写算法.计算机应用,2012,32(9): 2568-2572
[12] Lu Zhongkang,Lin Weisi,Yang Xiaokang,et al. Modeling Visual Attention′s Modulatory after Effects on Visual Sensitivity and Quality Evaluation. IEEE Trans on Image Processing,2005,14(11): 1928-1942
[13] Lee K W,Buxton H,Feng Jianfeng. Cue-Guided Search: A Computational Model of Selective Attention. IEEE Trans on Neural Networks,2005,16(4): 910-924
[14] Itti L,Koch C,Niebur E. A Model of Saliency-Based Visual Attention for Rapid Scene Analysis. IEEE Trans on Pattern Analysis and Machine Intelligence,1998,20(11): 1254-1259
[15] Harel J,Koch C,Perona P. Graph-Based Visual Saliency // Schlkopf B,Platt J,Hofmann,T,eds. Advances in Neural Information Processing Systems 19. Cambridge,UK: MIT Press,2007: 545-552
[16] Yu Ying,Wang Bin,Zhang Liming. Selective Visual Attention Model Based on Pulsed Cosine Transform. Pattern Recognition and Artificial Intelligence,2010,23(5): 616-623 (in Chinese)
(余 映,王 斌,张立明.基于脉冲余弦变换的选择性视觉注意模型. 模式识别与人工智能,2010,23(5): 616-623)
[17] Hou Xiaodi,Harel J,Koch C. Image Signature:Highlighting Sparse Salient Regions. IEEE Trans on Pattern Analysis and Machine Intelligence,2012,34(1): 194-201
[18] Guo Chenlei,Zhang Liming. A Visual Memory Model with Amnesic Function and Its Application in Attention Selection.Pattern Recognition and Artificial Intelligence,2008,21(3): 381-387 (in Chinese)
(过晨雷,张立明.带有遗忘的视觉记忆模型及其在注意力选择上的应用.模式识别与人工智能,2008,21(3):381-387)
[19] Vaisey J,Gersho A. Image Compression with Variable Block Size Segmentation. IEEE Trans on Signal Processing,1992,40(8): 2040-2060
[20] Dou Yan,Kong Lingfu,Wang Liufeng. A Computational Model of Visual Attention Based on Visual Entropy. Acta Optica Sinica,2009,29(9): 2511-2515(in Chinese)
(窦 燕,孔令富,王柳锋.基于视觉熵的视觉注意计算模型.光学学报,2009,29(9): 2511-2515)
[21] Chan C K,Cheng L M. Hiding Data in Images by Simple LSB Substitution. Pattern Recognition,2004,37(3): 469-474
[22] Watson A B.DCT Quantization Matrices Visually Optimized for Individual Images // Proc of the International Society for Optical Engineering. Washington D C,USA,1993: 202-216
[23] Mayache A,Eude T,Cherifi H. A Comparison of Image Quality Models and Metrics Based on Human Visual Sensitivity // Proc of the International Conference on Image Processing. Chicago,USA,1998,Ⅲ: 409-413
[24] Zhou Wang,Bovik A C,Sheikh H R,et al. Image Quality Assessment: From Error Visibility to Structural Similarity. IEEE Trans on Image Processing,2004,13(4): 600-612
[25] Ma Qi,Zhang Liming. A Fast Computation of Attention Selection Map and Its Application in Image Quality Assessment. Journal of Computer-Aided Design Computer Graphics,2009,21(7): 973-983(in Chinese)
(马 奇,张立明.快速注意力选择计算及其在图像质量评价中的应用.计算机辅助设计与图形学学报,2009,21(7): 973-983) |
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2013, Vol. 26 
