实验技术与管理2025，Vol.42Issue(7)：66-78,13.DOI:10.16791/j.cnki.sjg.2025.07.009
基于多特征融合匹配与多条件约束构面的轮廓线重建算法
Contour line reconstruction algorithm based on multifeature fusion matching and multicondition-constraint surface construction
摘要
Abstract
[Objective]The geological surface reconstruction method based on contour line data has been widely adopted due to its efficiency and accuracy.Specifically,the contour reconstruction technique utilizing feature point matching and mesh partitioning has become a critical research focus in this field because of its excellent performance.However,existing feature point matching methods often exhibit inadequate robustness and accuracy when dealing with complex geological structures and noisy data.Additionally,current triangulation algorithms face significant challenges in generating high-quality triangular meshes,such as in avoiding elongated and narrow triangles and ensuring uniform distribution without self-intersections.This study aims to address these issues by proposing a novel contour line reconstruction algorithm that integrates multifeature fusion matching with multicondition-constraint surface construction,thereby enhancing the accuracy and reliability of geological surface reconstructions.[Methods]To overcome the limitations of multifeature constraints and the local defects of fuzzy matching algorithms,this paper proposes the mentioned algorithm.First,a similarity quantification evaluation method based on spatial quadrilaterals is introduced,defining four feature measures to enhance robustness and compensate for the shortcomings of basic triangular patches in capturing feature point adjacency information and orientation constraints.Principal component analysis is employed for feature fusion and optimal solution computation,with principal components selected based on cumulative contribution rates.The dissimilarity between matching point pairs is defined using Euclidean distance,establishing a robust matching relationship.Second,a secondary matching mechanism incorporating distance weights and inflection point detection is proposed to mitigate the impact of locally unreasonable matches.Finally,to address the inadequacies of existing triangulation algorithms during the tiling process,an adjacency surface roughness function is defined to assess the quality of adjacent triangles.Surface construction is then performed based on this quality assessment,ensuring the smoothness and detail-capture ability of the involved triangular mesh.[Results]Experimental results demonstrate that the proposed algorithm achieves reasonable outcomes in modeling geological exploration Contour Profile data and geophysical inversion profile data.By introducing multiple feature measures and optimization mechanisms,the accuracy and robustness of contour line reconstruction are significantly improved compared to conventional approaches including global optimal constraint matching and local optimal constraint matching.Notably,when handling complex geological structures and noisy data,the new algorithm exhibits higher adaptability and stability.Thereby enhancing the overall quality of the reconstructed models.[Conclusions]This study provides a robust and efficient solution for geological surface reconstruction through theoretical innovation and methodological improvements,significantly enhancing the accuracy and reliability of geological structure models.It offers substantial support for fields such as resource exploration,environmental monitoring,and disaster prevention.关键词
地质表面重建/轮廓线重建/多特征匹配/PCA融合Key words
geological surface reconstruction/contour reconstruction/multifeature matching/principal component analysis fusion分类
天文与地球科学引用本文复制引用
姚锦鹏,简楚,朱四新,周赫,邓佳悦,何孟语,简兴祥..基于多特征融合匹配与多条件约束构面的轮廓线重建算法[J].实验技术与管理,2025,42(7):66-78,13.基金项目
四川省地质矿产勘查开发局2025年度科技项目(SCDZ-KJXM202503) （SCDZ-KJXM202503）
国家自然科学基金项目(42274132) （42274132）
四川省科技项目(24ZHSF0299) （24ZHSF0299）
