Perceptual Copyright Protection Using Multiresolution Wavelet-Based Watermarking And Fuzzy Logic

TL;DR

This paper introduces a novel DWT-based watermarking method utilizing fuzzy logic to select high-entropy coefficients for embedding, enhancing robustness and transparency without needing the original image.

Contribution

It proposes a fuzzy inference-driven watermarking technique that embeds in high-entropy coefficients of coarser DWT subbands, improving robustness and transparency over previous methods.

Findings

Effective resistance to image-processing attacks like smoothing and JPEG compression

High image transparency and robustness demonstrated

No need for original image during watermark extraction

Abstract

In this paper, an efficiently DWT-based watermarking technique is proposed to embed signatures in images to attest the owner identification and discourage the unauthorized copying. This paper deals with a fuzzy inference filter to choose the larger entropy of coefficients to embed watermarks. Unlike most previous watermarking frameworks which embedded watermarks in the larger coefficients of inner coarser subbands, the proposed technique is based on utilizing a context model and fuzzy inference filter by embedding watermarks in the larger-entropy coefficients of coarser DWT subbands. The proposed approaches allow us to embed adaptive casting degree of watermarks for transparency and robustness to the general image-processing attacks such as smoothing, sharpening, and JPEG compression. The approach has no need the original host image to extract watermarks. Our schemes have been shown to provide very good results in both image transparency and robustness.