Development of Efficient Watermarking Techniques in Medical Images

Abstract

Watermarking techniques are widely used for copyright protection, confidentiality and integrity issues in medical field. There are various watermarking techniques for hiding crucial patient s data while digital medical image transmission but most lack resistance against many unwanted attacks. There is a greater need for prevention of unauthorized access and tampering of medical may lead to misdiagnosis and wrongful treatment and can also influence the life of a human being. Reversibility, robustness, embedding capacity and invisibility are the essential requirements of a watermarking technique. This research proposes four different robust and reversible watermarking techniques for medical image watermarking. Cogitating the need of security for medical images, this first technique, proposes a reversible high embedding capacity, high image fidelity, a hybrid robust lossless data hiding technique by using both transform and spatial domains. Proposed technique alters the mean of the selected non-overlapping slantlet transformed blocks of the host image whereas RS vector considers flipping factor for data embedding. The optimum thresholds to select the blocks are calculated through Particle Swarm Optimization (PSO) technique and watermark is generated by using patient details, biometric Identification (ID) and Region Of Interest (ROI) blocks of host image. This watermark is further compressed by applying Lempel-Ziv-Welch (LZW) technique and encrypted by Advanced Encryption Standard (AES) as well as Message Digest Algorithm 5 (MD5). The watermark bits are embedded in all three Red Green Blue (RGB) channels of a cover image, to increase the embedding capacity up to 3.3675 Bit Per Pixel (bpp). The second proposed technique is a hybrid robust lossless data hiding algorithm that uses the Singular Value Decomposition (SVD) with Fast Walsh Transform (FWT) and Slantlet Transform (SLT) for image authentication. These transforms have good energy compaction with distinct filtering, which leads to higher embedding capacity from 1.8