A Correlation-Based Watermarking Technique of 3-D Meshes via Cyclic Signal Processing

Abstract

This paper describes a blind watermarking scheme through cyclic signal processing. Due to various rapid networks, there is a growing demand of copyright protection for multimedia data. As efficient watermarking of images, there exist two major approaches: a quantization-based method and a correlation-based method. In this paper, we proposes a correlation-based watermarking technique of three-dimensional (3-D) polygonal models using the fast Fourier transforms (FFTs). For generating a watermark with desirable properties, similar to a pseudonoise signal, an impulse signal on a two-dimensional (2-D) space is spread through the FFT, the multiplication of a complex sinusoid signal, and the inverse FFT. This watermark, i.e., spread impulse signal, in a transform domain is converted to a spatial domain by an inverse wavelet transform, and embedded into 3-D data aligned by the principle component analysis (PCA). In the detection procedure, after realigning the watermarked mesh model through the PCA, we map the 3-D data on the 2-D space via block segmentation and averaging operation. The 2-D data are processed by the inverse system, i.e., the FFT, the division of the complex sinusoid signal, and the inverse FFT. From the resulting 2-D signal, we detect the position of the maximum value as a signature. For 3-D bunny models, detection rates and information capacity are shown to evaluate the performance of the proposed method.