摘要
针对图像的真实性和完整性认证 ,提出一种基于神经网络的脆弱水印技术 首先 ,随机选取一些像素及它们的邻域 ;然后 ,用神经网络建立这些像素点与它们邻域中的其它像素点之间的关系模型 ,最后 ,通过调整被选像素点与模型输出值之间的大小关系来嵌入水印图案的位信息 根据提取的水印图案 ,可以判断被检测的图像是否真实以及被篡改的位置 实验结果表明 ,该技术在保持较高图像质量的前提下 ,具有安全性能好。
For authenticating an image, this paper proposes a neural network-based fragile watermarking scheme. In the proposed method, we select some pixels and their vicinities randomly, and then establish the relational model among these pixels and other pixels in their vicinities using the neural network. Finally we embed a bit information of the watermark by adjusting the polarity between a selected pixel and the output value of the model. According to the extracted watermark, we can authenticate the tested image and locate the illegal modification. Experimental results show the proposed method has some advantages such as security, high sensitivity and exactly locating the modifications, while still keeping high quality of the image.
出处
《计算机辅助设计与图形学学报》
EI
CSCD
北大核心
2003年第3期307-312,共6页
Journal of Computer-Aided Design & Computer Graphics
基金
广东省自然科学基金 ( 0 2 0 199)
广东省教育厅自然科学基金(Z0 2 0 42 )资助
关键词
脆弱水印
数字图像
真实性鉴定
神经网络
fragile watermark
digital image
authenticity
neural networks
