PROJECT TITLE :

An Adaptive Digital Image Watermarking Scheme with PSO, DWT and XFCM - 2017

ABSTRACT:

In this paper, a completely unique adaptive digital image watermarking model primarily based on modified Fuzzy C-means that Clustering is proposed. For watermark embedding method, we have a tendency to used Discrete Wavelet Transform (DWT). A segmentation technique XieBeni integrated Fuzzy C-suggests that clustering (XFCM) is used to spot the segments of original image to reveal suitable locations for embedding watermark. We tend to additionally pre-processed the host image using Particle Swarm Optimization (PSO) to be in agreement to the clustering process. The goal is to target correct segmentation of the image therefore that the embedded watermark will face up to common Image Processing attacks and offer security to digital images. Several attacks were performed on the watermarked images and original watermark was extracted. Performance measures like PSNR, MSE, CC were computed to test the extracted watermarks with and while not attacks. Experimental results show that the proposed theme has performed well in terms of imperceptibility and robustness when compared to other watermarking models.