| Tomography scanning data is an important data source in the reverse engineering. With thedevelopment of reverse engineering, feature-based modeling becomes the bright way of the threedimensional model reconstruction. The feature line extraction of cross section line data based ontomography image has become one of the important basic technology in reverse engineering. Thisthesis deeply studied in the feature line extraction from complicated section curve data through CSS(Curvature Scale Space) algorithm and Voronoi image. The main content and creative achievement ofthis thesis is described as follows:(1) The feature point extraction technique of complicated section curve data is studied. Firstly，introduce the curvature scale space theory of contour curves, then calculate the curvature of theevolution curve to get extremum curvature points in different scales. Finally, we get the feature pointsthrough the analysis of the CSS image.(2) The connection of feature line method generated by the feature points is studied. Improve thegrowth direction and scale based on the basic line generation algorithm, then present improvedpolyline generation algorithm. We study and analy the bifurcation problems in the process of foldencountered growing up and propose the corresponding solutions.(3) We have studied the generation method of Voronoi generation diagram of complicated sectioncurve data.Make a depth-analysis of the grid growing algorithm implementation process inthree-dimensional model space. Present the analysis of the situation of the neighborhood growth in thebifurcation begining layer, the bifurcation intermediate layer, the bifurcation ending layer and notbifurcation layer.These algorithms in this thesis have been programmed, and a system for feature line extractionand feature network contruction of the complicated section curve data has been established. Manynumerical tests show that algorithms in this thesis are effective and stable. |
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