A Novel Image Watermarking Technique Using Fuzzy-BP Network

In this paper, Human Visual System (HVS) characteristics are modeled using Lee and Lu´s Fuzzy- BP network for the purpose of image watermarking. The Fuzzy-BP network is trained by 27 inference rules comprising of three input HVS features namely luminance sensitivity, edge sensitivity computed using threshold and contrast sensitivity computed using variance. The Fuzzy-BP network block wise produces a single output weighting factor which is used to embed two different watermarks - (a) a sequence of normalized random numbers and (b) a binary image, with in the host image in the transform (DCT) domain. The high computed value of PSNR parameter indicates that the signed image has good perceptible quality. The watermark is extracted from the signed image using Cox´s algorithm. The embedded and extracted watermarks are compared and SIM(X, X*) correlation parameter is computed.