| Citation: | YAO Jinpeng，JIAN Xingxiang，ZHOU He，et al. Complex contour reconstruction of geological bodies based on fuzzy matching and multi-feature constrained interpolation[J]. Bulletin of Geological Science and Technology，2026，45（3）：1-13 doi: 10.19509/j.cnki.dzkq.tb20240606
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To address the problems of low matching accuracy, topological distortion, and geometric deformation caused by significant contour feature differences in adjacent geological body contour reconstruction, and to overcome the limitations of full-mapping matching, this study proposes a complex contour reconstruction algorithm based on fuzzy matching and multi-feature constrained interpolation.
Initially, the method integrated vertex spatial positions, local adjacency relationships, and global contour features to establish a fuzzy-domain matching strategy. Vertex similarity between adjacent contours was evaluated, and one-to-one mappings between similar vertices were constructed. Based on the matching results, maximum proximity contours between the source and target contours were generated. Subsequently, linear interpolation and discrete polygon evolution were applied to handle transitional shapes between maximum proximity contours and between original and maximum proximity contours, respectively. Finally, three-dimensional reconstruction was performed on the interpolated contour sequence based on the matching results, using bounding-box-constrained geometric transformation correction. Reconstruction tests were conducted using three sets of typical geological exploration-line profile data. The standard GOCAD reconstruction algorithm was selected as the baseline, and improved algorithms with local and global optimization constraints were introduced for systematic comparison.
The results showed that the proposed method effectively resolved the problems of contour self-intersection and topological disorder in conventional reconstruction approaches. Evaluations using a geometric assessment system—comprising triangle similarity, span length, and spatial angles—demonstrated that the reconstructed triangulated irregular network (TIN) models exhibited significant advantages in geometric accuracy and topological consistency.
The proposed approach reduces the dependency of contour interpolation on matching results and provides both algorithmic innovation and theoretical references for addressing correspondence and interpolation problems in contour reconstruction.
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