Adaptive image watermarking using human perception based fuzzy inference system
Journal of Intelligent & Fuzzy Systems, 2018•content.iospress.com
Abstract Development of digital content has increased the necessity of copyright protection
using watermarking. Imperceptibility and robustness are two important features of
watermarking algorithms. The goal of watermarking methods is to satisfy the tradeoff
between these two contradicting characteristics. Recently, watermarking methods in
transform domains have displayed favorable results. In this paper, we present an adaptive
blind watermarking method, which has high imperceptibility in areas that are important to the …
using watermarking. Imperceptibility and robustness are two important features of
watermarking algorithms. The goal of watermarking methods is to satisfy the tradeoff
between these two contradicting characteristics. Recently, watermarking methods in
transform domains have displayed favorable results. In this paper, we present an adaptive
blind watermarking method, which has high imperceptibility in areas that are important to the …
Abstract
Development of digital content has increased the necessity of copyright protection using watermarking. Imperceptibility and robustness are two important features of watermarking algorithms. The goal of watermarking methods is to satisfy the tradeoff between these two contradicting characteristics. Recently, watermarking methods in transform domains have displayed favorable results. In this paper, we present an adaptive blind watermarking method, which has high imperceptibility in areas that are important to the human visual system. We propose a fuzzy system to control the embedding strength factor adaptively. Image saliency, intensity, and edge-concentration are shown to be important to a human observer and are hence used as fuzzy attributes. Embedding is performed in the discrete cosine transform of the wavelet domain to achieve high imperceptibility and acceptable robustness. Experimental results show the superiority of the proposed algorithm over comparable methods.
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