A New Robust Zero-watermarking Algorithm for Medical Volume Data

Abstract

Aiming at medical image information security problem, this paper proposes a new robust zero-watermarking algorithm for medical volume data based on three-dimensional discrete wavelet transform, three-dimensional Fourier transform and hermite chaotic neural network . Firstly, it employs a novel hermite chaotic neural network to generate the pseudo-random chaotic sequence for scrambling. Secondly, three dimensional medical image is transformed by three-dimensional discrete wavelet transform and three-dimensional discrete Fourier transform. Then, select the transformed low and intermediate frequency coefficients symbol as medical volume data characteristics to structure zero-watermarking. The algorithm integrates hermite chaotic neural network and zero-watermarking technology, which is not confined to artificially selected region of interest. The watermarking extraction does not need the original image. And its security depends on the chaotic sequence complexity and unpredictability, solving the watermark embedding, extraction safety and efficiency. The simulation results show that the algorithm is simple to implement, with good robustness, security and invisibility.