Curvature Gradient-estimation Using CT Sinogram and its Application to Reverse Engineering. (July 2022)

• Record Type: Journal Article
• Authors: Suzuki, Shintaro; Ohtake, Yutaka; Suzuki, Hiromasa
• Is Part Of: Computer aided design. Volume 148(2022)
• Publication Date: 2022-07
• Subjects: Reverse engineering -- X-ray CT -- Sinogram -- Curvature gradient -- Segmentation -- Morse theory; Computer-aided design -- Periodicals; Engineering design -- Data processing -- Periodicals; Computer graphics -- Periodicals; Conception technique -- Informatique -- Périodiques; Infographie -- Périodiques; Computer graphics; Engineering design -- Data processing; Periodicals; Electronic journals; 620.00420285
• DOI: 10.1016/j.cad.2022.103240
• Languages: English
• ISSNs: 0010-4485

Abstract

Abstract: 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. Highlights: Robust curvature gradients are computed directly from CT sinogram. Flexible and powerful segmentation is performed using multi-level Morse complex. B-spline surfaces are patched onto each segmented region as a demonstration. X-ray CT simulations are conducted and used for the proposed method.