  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.
