基于主成分分析的水印图像识别

Amol R. Madane, M. M. Shah
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引用次数: 2

摘要

提出了一种基于离散小波变换(DWT)的数字图像水印算法。采用小波变换后的二级主图像细节系数作为水印密钥进行水印标识的插入或添加和提取。我们提出了在图像识别中使用主成分分析(PCA)学习低维表示的方法。它基于图像集的二阶统计量。主成分分析的目的是寻找模式的二阶相关性。测试了PCA对原始水印的有效性,提取了水印。我们能够设计一个原型系统,它提供用户身份验证。所提出的水印图像识别系统可以应用于身份识别系统、文件控制和访问控制中。
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Watermark Image Recognition Using Principal Component Analysis
In this paper, the algorithm of digital image watermarking is proposed using discrete wavelet transform (DWT) for copyright protection. The detail coefficients of second level host image after taking DWT is used as a watermark key for the watermark logo insertion or addition and extraction process. We have proposed the learning of low dimensional representation in the context of image recognition using principle component analysis (PCA). It is based on the second order statistics of image set. The PCA aims to find second order correlation of patterns. The effectiveness of PCA is tested on original watermark logo, extracted watermark logo. We were able to design a prototype system, which provides user authentication. The proposed system of watermark image recognition may be applied in identification systems, document control and access control.
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