In industrial manufacturing, reverse engineering, which can be applied to analyze or re-design, is an essential process, whereby scanned data of real objects are used to generate a CAD model. CAD data have various features such as fillets; therefore, robust and versatile reverse engineering is still difficult. Particularly, an adequate segmentation from real scanned data is challenging, and it is a major obstacle for reverse engineering. In this study, we propose an innovative segmentation from CT scanned data, wherein user-friendly segmentation is achieved by directly computing the curvature gradient from a CT sinogram. We used the proposed method to patch a B-spline surface onto each segmented region. The experimental results show that the proposed method offers robust, versatile, and user-friendly reverse engineering that is faster than conventional manual modeling. In addition, as it is supported by X-ray CT simulation, the proposed method can be applied to various surface mesh data without requiring any actual X-ray CT equipment.

In this paper, a method of copyright monitoring or tracing using invariants of contents is proposed. We first define certain feature parameters of color images which are invariant under arbitrary bicontinuous or smooth transforms, called topological or differentially topological invariants. To extract the topological invariants robustly, we introduce scale-space of invariant features. By selecting topologically stable features with respect to scale transform, noise-robust invariants of images are obtained. These invariants can be applied to copyright tracing or monitoring and protection due to their robustness against various deformation attacks.