摘要
提出了基于人工神经网络的半脆弱零水印技术。首先在宿主图像中随机选择像素点,然后利用神经网络构建所选择像素点与其3×3邻域像素之间的关系,并与二值水印图像进行异或运算得到水印检测密钥,作为所构造的零水印。由于仅从宿主图像中抽取特征构造水印,而没有向图像中嵌入信息,避免了嵌入水印所导致的图像变形。该技术可以用于图像真实性、完整性认证,并可定位篡改发生的位置,且对于JPEG图像压缩具有一定的稳健性。实验结果证明了算法的有效性。
An artificial neural network based semi-fragile watermarking scheme for image authentication is proposed.Firstly,some pixels are selected randomly from the host image.Then,the neural network technique is utilized to model relationships between the randomly selected pixels and their 3×3 neighboring pixels.By applying the exclusive-or （XOR） operation to the modeled relationships and the binary watermark image, a secret key for watermark recovery is obtained as the constructed zero-watermark. Since only the image features are extracted from the host image to construct watermark instead of embedding information to the image,avoiding image distortion resulting from watermark embedding.The proposed scheme achieves tamper detection as well as tampered position localization,in addition to the image credibility authentication,while being robust to JPEG compression at a certain degree.The experimental results demonstrate the effectiveness of the proposed scheme.
出处
《计算机工程与应用》
CSCD
北大核心
2009年第16期93-95,164,共4页
Computer Engineering and Applications
基金
广东省教育部产学研结合项目(No.2007B090400121)
关键词
人工神经网络
零水印
半脆弱
图像认证
篡改定位
artificial neural networks
zero-watermark
semi-fragile
image authentication
tamper localization
