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Digital planar surface segmentation using local geometric patterns

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (2008) 4992 LNCS 322-333
DOI: 10.1007/978-3-540-79126-3_29
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Abstract

This paper presents a hybrid two-step method for segmenting a 3D grid-point cloud into planar surfaces by using discrete-geometry results. Digital planes contain a finite number of local geometric patterns (LGPs). Such a LGP possesses a set of normal vectors. By using LGP properties, we first reject non-linear points from a point cloud (edge-based step), and then classify non-rejected points whose LGPs have common normal vectors into a planar-surface-point set (region-based step). © 2008 Springer-Verlag Berlin Heidelberg.

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APA

Kenmochi, Y., Buzer, L., Sugimoto, A., & Shimizu, I. (2008). Digital planar surface segmentation using local geometric patterns. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 4992 LNCS, pp. 322–333). https://doi.org/10.1007/978-3-540-79126-3_29

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