[Paper] Automatic Detection of Sharp Edges from Point Cloud Using Surface Universality Rating

• Published in: ITE TRANSACTIONS ON MEDIA TECHNOLOGY AND APPLICATIONS Vol. 12; no. 1; pp. 9 - 21
• Main Authors: Erdenebayar, Shurentsetseg, Konno, Kouichi, Altantsetseg, Enkhbayar
• Format: Journal Article
• Language: English
• Published: The Institute of Image Information and Television Engineers 2024
• Subjects: automatic detection; covariance feature; feature point; point cloud; sharp edges; surface sharpness; Surface Universality Rating; T-point method
• ISSN: 2186-7364; 2186-7364
• DOI: 10.3169/mta.12.9

In this paper, we introduce the Surface Universality Rating (SUR) method to accurately measure surface sharpness from a point cloud. Moreover, this study represents the first attempt to distinguish edge points automatically. The easy and accurate evaluation of surface sharpness is a critical challenge associated with point cloud processing. Although surface sharpness is an essential property for shape analysis, local analytical methods for the evaluation of surface properties exhibit limitations in terms of geometric shape. Furthermore, local analyses are insufficient for evaluating the sharpness of edge points owing to the scarcity of neighboring points. These challenges require more accurate assessments of surface sharpness, as well as more efficient thresholding for feature points. Although many methods have been developed to evaluate surface sharpness, they are generally difficult to use and require many parameters. We conducted experiments to verify the effectiveness of our method.