Automatic segmentation of the apparent contour for 3D modeling of cutting tools from single view

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Abstract

One of the industrial applications for vision-based model reconstruction of surfaces of revolution (SOR) is to rebuild 3D models of rotating mill cutters. For this application, the automation of the process is crucial. One of the critical issues with the automation is the segmentation of the apparent contour. Therefore, this paper introduces a new approach for the automatic apparent contour extraction of SORs. It consists of three parts. Firstly, the region of SOR is located on image and the contour of SOR is extracted inside this region. Secondly, the extracted contour is partitioned into several portions based on curvature analysis. A property of SOR is used to verify the partitioning. Finally, the contour is classified into the apparent contours and the imaged cross sections by exploiting both 2D and 3D information. The experiment on machine tool verifies that the algorithms proposed are reliable and accurate in the industrial environment. © 2008 Springer Berlin Heidelberg.

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Zhang, X., Tsang, W., Tian, X., Yamazaki, K., & Mori, M. (2008). Automatic segmentation of the apparent contour for 3D modeling of cutting tools from single view. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 5359 LNCS, pp. 772–781). https://doi.org/10.1007/978-3-540-89646-3_76

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