SVD on a Robust Medical Image Watermarking based on SURF and DCT

Abstract

Communication technology, multimedia, copyright protection, content data have gained attention in recent years. In addition, privacy and confidentiality are also major challenges in handling. A robust hybrid based on speeded-up robust features (SURF), discrete cosine transform (DCT), singular value decomposition or SVD, and chaotic (Arnold's Cat Map) scheme is proposed in this paper. The use of chaotic maps is for watermarking medical images, which can provide protection and security on medical images. In the watermark image, a method is applied that will increase the security of the watermark image, namely Arnold's Cat Maps. SVD method is used to decompose input data into three submatrices. To produce a watermarked image by combining the watermark image and the host image with the SURF-DCT-SVD method, the embedding stage is carried out. At the extraction stage, it will produce a watermark image from the watermarked image. Furthermore, various attacks were carried out against the proposed method. Experimental results show SVD can increase the robustness of DCT and SURF-based watermarking schemes. The proposed watermarking technique is resistant to JPEG compression attacks, noise addition, signal processing, and geometry attacks. In addition, the other state-of-the-art techniques are compared to the performance of the proposed method. Thus, the proposed watermarking scheme can protect ownership and medical records of medical images.