Proceedings of the
9th International Conference of Asian Society for Precision Engineering and Nanotechnology (ASPEN2022)
15 – 18 November 2022, Singapore
doi:10.3850/978-981-18-6021-8_OR-05-0288
High accuracy alignment of X-ray CT volumewith CAD data using feature vectors
1Department of Mechanical Systems Engineering, Tokyo Metropolitan University, 6-6 Asahigaoka, Hino-shi, Tokyo, Japan
ABSTRACT
We present an algorithm to accurately align CAD data to X-ray CT scan data (CT volume). CT volume is a 3D image, so it does not have explicitly defined surface points. The core idea of our algorithm is to extract feature points from CT volume and CAD data, and align them by optimization using feature vectors assigned to the feature points. The feature vectors represent the shape around the feature points. The optimization minimizes the geometric differences between the CT volume and CAD data expressed by their feature vectors. Experiment for CT volumes of assembly product show that the two data can be aligned with a higher accuracy with the proposed algorithm than other methods based on iterative closest point.
Keywords: CT volume, CAD surface, alignment, feature vectors, feature points
1Department of Mechanical Systems Engineering, Tokyo Metropolitan University, 6-6 Asahigaoka, Hino-shi, Tokyo, Japan
ABSTRACT
We present an algorithm to accurately align CAD data to X-ray CT scan data (CT volume). CT volume is a 3D image, so it does not have explicitly defined surface points. The core idea of our algorithm is to extract feature points from CT volume and CAD data, and align them by optimization using feature vectors assigned to the feature points. The feature vectors represent the shape around the feature points. The optimization minimizes the geometric differences between the CT volume and CAD data expressed by their feature vectors. Experiment for CT volumes of assembly product show that the two data can be aligned with a higher accuracy with the proposed algorithm than other methods based on iterative closest point.
Keywords: CT volume, CAD surface, alignment, feature vectors, feature points
