Dual hybrid medical watermarking using walsh-slantlet transform

Abstract

A hybrid robust lossless data hiding algorithm is proposed in this paper by using the Singular Value Decomposition (SVD) with Fast Walsh Transform (FWT) and Slantlet Transform (SLT) for image authentication. These transforms possess good energy compaction with distinct filtering, which leads to higher embedding capacity from 1.8 bit per pixel (bpp) up to 7.5bpp. In the proposed algorithm, Artificial Neural Network (ANN) is applied for region of interest (ROI) detection and two different watermarks are created. Embedding is done after applying FWH by changing the SVD coefficients and by changing the highest coefficients of SLT subbands. In dual hybrid embedding first watermark is the ROI and another watermark consists of three parts, i.e., patients’ personal details, unique biometric ID and the key for encryption. Comparison of the proposed algorithm is done with the existing watermarking techniques for analyzing the performance. Experiments are simulated on the proposed algorithm by casting numerous attacks for testing the visibility, robustness, security, authenticity, integrity and reversibility. The resultant outcome proves that the watermarked image has an improved imperceptibility with a high level of payload, low time complexity and high Peak Signal to Noise Ratio (PSNR) against the existing approaches.