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Orebody Modeling from Non-Parallel Cross Sections with Geometry Constraints

1,2, 1,2, 1,2, 1,2,* and 1,2
1
School of Resources and Safety Engineering, Central South University, Changsha 410083, China
2
Research Center of Digital Mine, Central South University, Changsha 410083, China
*
Author to whom correspondence should be addressed.
Minerals 2019, 9(4), 229; https://doi.org/10.3390/min9040229
Received: 15 March 2019 / Revised: 29 March 2019 / Accepted: 10 April 2019 / Published: 12 April 2019
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Abstract

In this paper, we present an improved approach to the surface reconstruction of orebody from sets of interpreted cross sections that allows for shape control with geometry constraints. The soft and hard constraint rules based on adaptive sampling are proposed. As only the internal and external position relations of sections are calculated, it is unnecessary to estimate the normal directions of sections. Our key contribution is proposing an iterative closest point correction algorithm. It can be used for iterative correction of the distance field based on the constraint rules and the internal and external position relations of the model. We develop a rich variety of geometry constraints to dynamically control the shape trend of orebody for structural geologists. As both of the processes of interpolation and iso-surface extraction are improved, the performance of this method is excellent. Combined with the interactive tools of constraint rules, our approach is shown to be effective on non-trivial sparse sections. We show the reconstruction results with real geological datasets and compare the method with the existing reconstruction methods. View Full-Text
Keywords: three-dimensional geomodeling; implicit modeling; radial basis functions; contours interpolation; distance field three-dimensional geomodeling; implicit modeling; radial basis functions; contours interpolation; distance field
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Zhong, D.-Y.; Wang, L.-G.; Jia, M.-T.; Bi, L.; Zhang, J. Orebody Modeling from Non-Parallel Cross Sections with Geometry Constraints. Minerals 2019, 9, 229.

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