Chaos-Based Semi-Blind Watermarking for CAD Models

Digital watermarking technique is becoming one of the hot research fields of copyright protecting, private detection for CAD graphic data under the network environment. But existing watermarking algorithms for polygonal meshes and their attributes can´t be applied to the majority of computer aided design (CAD) applications, for two major reasons. First, these CAD systems employ parametric curves and surfaces, not polygonal meshes, as their main shape- defining primitives. Second, most CAD applications do not tolerate modifications of model topology and/or geometry that are introduced by existing watermarking algorithms. In this paper we propose a watermarking mechanism for CAD models, those employ non-uniform rational B-spline (NURBS) curves and surfaces as their main shape-defining primitives. This mechanism using relative knot insertion method embeds the watermarks generated by chaotic map into the NURBS primitives, and it exactly preserves the shapes. Since it is a semi-blind watermarking algorithm, we need just the original message to extract the watermarks from the watermarked models, and after comparing them with the original one we can tell whether there is the watermark in this CAD model upon the similarity. The experimental results shows that our watermarking mechanism is robust against most common attacks.