A 3-D Mesh Watermarking Scheme with Highpass Filter

Abstract

In this paper, we investigate a blind watermarking algorithm based on a highpass filter for three-dimensional (3-D) meshes. For improving watermark detection in correlationbased watermarking, our scheme employs the highpass filter which emphasizes an impulse signal embedded as a signature into a host mesh. In the proposed method, we align the host mesh by the principal component analysis and convert from orthogonal coordinates to polar coordinates. After this preprocessing, we map the 3-D data onto a 2-D space via block segmentation and average operation, and rearrange for the 2-D data to an 1-D sequence. On the 1-D space, we apply a complex smear transform and a highpass filter. From the resulting signal, we derive the optimum complex-valued impulse signal in terms of the Euclidean norm. To generate a watermark with desirable properties, similar to a pseudonoise signal, we perform a complex desmear transform, which is the inverse system to the complex smear transform, on the complex-valued impulse signal. After reordering into the 2-D signal and 3-D mapping from the 2-D space, the watermark is embedded into the host mesh and the resulting mesh is converted to orthogonal coordinates. At the decoder, we implement an inverse process with the highpass filter for stego meshes and detect a position of the maximum value as a signature. For a 3-D Bunny model, detection rates are shown to evaluate the performance of the proposed algorithm.

Homomorphic encryption domain asymmetric fingerprinting scheme for 3D models of oblique photography

“…The proposed scheme was compared with two other representative schemes (Taniguchi & Uto, 2017; Wang et al., 2018) in terms of the coordinate errors after information embedding. Looking at the error statistics data in Table 3, it can be observed that the Root Mean Square Error and Maximum Error for the four models after embedding fingerprint information in the proposed scheme are both less than 0.00001.…”