Abstract
Features are significantly used as design elements to reconstruct a model in reverse engineering. This paper proposes a new method for detecting corner features and edge features in 3D from CT scanned data. Firstly, the level set method is applied on CT scanned data to segment the data in the form of implicit function having two values, which mean inside and outside of the boundary of the shape. Next, corners and sharp edges are detected and extracted from the boundary of the shape. The corners are detected based on Sobel-like mask convolution processing with a marching cube. The sharp edges are detected based on Canny-like mask convolution. In this step, a noisy removal module is included. In the paper, the result of detecting both features is presented.
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Ma, TC. et al. (2011). Features Detection on Industrial 3D CT Data. In: Kim, Th., et al. Multimedia, Computer Graphics and Broadcasting. MulGraB 2011. Communications in Computer and Information Science, vol 263. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-27186-1_48
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DOI: https://doi.org/10.1007/978-3-642-27186-1_48
Publisher Name: Springer, Berlin, Heidelberg
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