Watermark Image Recognition Using Principal Component Analysis

Abstract

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.