Research On Key Technology Of Irregular Fragments Reassembly

Lots of irregular fragment examples have existed in real world, some of which has great value, so people hope to reassembly them. Introducing computer aided technique to the field of fragment assembly has greatly speeded the assembly working process. This thesis has studied deeply on irregular fragment assembly methods, which include key techniques such as fragment digitalization, global and local feature extraction, fragment classification, fragment matching, and fragment assembly, these techniques can be employed in some other fields such as computer vision, reverse engineering, clinic medicine. Its main contents and contributions are as follows:3D fragment digistization technique and classification technique have been researched. First of all, optical scanner is used to to acquire the fragments'3D point cloud data. After data preprocessing, triangle mesh models of the fragments are constructed from STL files. Based on the proposed fragment classification methodology by thickness, the classification techniques targeting on revolved fragments are furtherly researched. According to the priori classification rule, which is based on feature point and feature metric, seed fragments are classified firstly. All the remained non-seed fragments are classified with profile matching method. A fragment library then has been constructed and used as the basis of the succesive fragment assembly work.Aiming at contour curve, a contour cuve matching strategy is proposed, which adopted two different matching methods according to the curve shape characteristic, namely, feature-based matching algorithm and segmentation-based matching algorithm. The feature-based matching algorithm estimates curvature by spline fitting, extracts the feature points, and obtain single-feature-point match, then constructed the similarity matrix, and searched the similarity matrix to obtain the multiple-feature-point match satisfying compability constraint. The algorithm improved the matching reliability. The segmentation-based matching algorithm has been used to contour curve with distinct corner point and obscured feature point. After contour segmentation and coarse matching, a dynamic algorithm is used to improve matching quality. The algorithm speeded the matching process and assured the matching quality.Aiming at thin walled fragment, a reassembly algorithm based on contour curve matching and triplet merging technique is proposed. Thin walled fragments included planar fragments and space revolving fragment. Firstly, the algorithm extracted boundary curve, used curve matching algorithm to do piecewise matching. Fragment assembly is completed based on triplets. The algorithm is characteristic of improving the reliability by auto-decision of curve direction and removal of fasle maching via simultaneous registration, overlapping detection and interference detection.Aiming at 3d non-thin walled fragments, a multiple-piece reassembly algorithm based on surface matching and sub-graph merging technique is proposed. The algorithm extracted the fracture region using feature-line-based segmentation method and optimized the frature region's boundary by snake model. A piecewise matching algorithm is proposed, which is the combination of maximum-clique surface matching and genetic algorithm. A multiple-piece assembly is proposed based on sub-graph merging technique. Bumping detection, global consistant detection and cross-boundary continuity dectection in the assembly process are used to romove the false matching.Aiming at 3d view pieces, a reference-point-independant multi-view reassembly algorithm is proposed. The algorithm uses the spin-image of high curvature point and uniform sampling point to do initial piecewise matching. Based on maximum weight clique, the initial matching point set is determined. Base on the minmum spanning tree, an enhanced ICP registration algorithm is proposed to do view pair's registration optimization and obtain the accurate matching point set. According to the accurate matching point set, an advanced SVD-based simultaneous registration method is proposed to minimize all the view-pair accumulated registration error.